Careers at AppFolio

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We are hiring a senior-level full-stack Software Engineer to join our Leasing Engineering Team and drive our rapid product development pace. We work collaboratively to define the technical direction for our SaaS products, developing high-quality, easy-to-use solutions for our customers. Our engineers take pride in delivering solutions that meaningfully impact customers and raise the technical bar for the organization. We balance pragmatism with excellence—delivering value quickly while ensuring systems are reliable, scalable, and maintainable. This is an ideal opportunity for someone who is passionate about building leading-edge software, thrives on solving complex technical problems, and wants to play a key role in shaping the success of a SaaS product used by thousands of businesses. We foster an environment that empowers small teams to take ownership, set the technical vision, and lead through impact. Responsibilities: Develop scalable, resilient, and elegant web-based solutions to solve complex business problems at scale. Lead by example in design, coding, and architecture; mentor and coach other engineers to raise the technical bar across the team. Formulate, implement, and optimize algorithms and database queries to ensure SaaS scalability, performance, and stability. Design and deliver new features and improve existing ones with a focus on robustness, maintainability, and performance. Drive engineering excellence through test-driven development, thoughtful code reviews, and continuous integration practices. Collaborate deeply with engineers, QA, product managers, designers, and researchers to deliver end-to-end solutions. Champion agile practices that emphasize collaboration, prioritization, urgency, and accountability to deliver at a rapid pace. Proactively research, share, and apply new technologies and patterns that improve system quality and accelerate delivery. You know you’re the right fit if… You have 5+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. You are comfortable working across all levels of the development stack and excel at breaking down complex problems. You have experience leading technical projects end-to-end—from shaping requirements and architecture through implementation, launch, and ongoing optimization—while aligning stakeholders and ensuring successful outcomes. You have experience with modern Agile software development practices (Scrum, Kanban, CI/CD). You have strong experience with automated testing and understand its role in sustainable engineering. You are language agnostic and have deep experience with at least one modern language such as Ruby, Java, or Python. You take a pragmatic approach to technology—adopting new tools where they add value, while mastering proven technologies. You care about long-term maintainability, advocate for clean architecture, and drive continuous refactoring and improvement. You balance intensity and sustainability—you’ll go the extra mile when needed but also model healthy work-life balance. Nice to Have: Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience with technologies in our stack such as Ruby on Rails, React, AWS, or service-oriented architectures. Experience with AI/ML technologies and how they integrate into SaaS applications. Experience leading architectural discussions, defining system design, and guiding technical decision-making. Compensation & Benefits The base salary that we reasonably expect to pay for this role is $138,400 - $173,000. The actual base salary for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, etc. Please note that base pay is one important aspect of a compelling Total Rewards package. The base pay range indicated here does not include any additional benefits or bonuses that you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products , and a core layer delivering intelligent, high-impact experiences directly to our customers . At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives —such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design. This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base. Your Impact ML Platform: Design and operate AppFolio's ML infrastructure on AWS — ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls. Drive AI Cost Discipline: Optimize cost across all AI applications — provider routing, caching, batch vs. real-time, model size selection, and inference economics. Multi-Provider Reliability: Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions. Training & Fine-Tuning Stack: Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation. Productionize Research: Partner with Voice & Agents and Research ML engineers to harden their prototypes into production systems with SLOs, on-call rotations, and observability. AI Safety & Guardrails: Operate AppFolio's AI safety and authorization layer — guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes. Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment. Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you. Sustainability: You value work-life balance as a foundation for sustained high performance. Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems. Must Have ML infra at scale: Has built and operated production ML infrastructure on AWS — ECS, SageMaker, GPUs, autoscaling, and cost controls. Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing. Provider breadth: Direct experience integrating with Google (Vertex / Gemini), OpenAI, and Anthropic APIs in production. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads. RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data. Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience training Small Language Models for production use. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Prior Staff-level role at a company with a significant AI infra footprint. Experience with ontology-driven systems or knowledge graphs supporting AI applications. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products , and a core layer delivering intelligent, high-impact experiences directly to our customers . At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives —such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design. This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base. Your Impact ML Platform: Design and operate AppFolio's ML infrastructure on AWS — ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls. Drive AI Cost Discipline: Optimize cost across all AI applications — provider routing, caching, batch vs. real-time, model size selection, and inference economics. Multi-Provider Reliability: Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions. Training & Fine-Tuning Stack: Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation. Productionize Research: Partner with Voice & Agents and Research ML engineers to harden their prototypes into production systems with SLOs, on-call rotations, and observability. AI Safety & Guardrails: Operate AppFolio's AI safety and authorization layer — guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes. Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment. Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you. Sustainability: You value work-life balance as a foundation for sustained high performance. Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems. Must Have ML infra at scale: Has built and operated production ML infrastructure on AWS — ECS, SageMaker, GPUs, autoscaling, and cost controls. Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing. Provider breadth: Direct experience integrating with Google (Vertex / Gemini), OpenAI, and Anthropic APIs in production. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads. RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data. Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience training Small Language Models for production use. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Prior Staff-level role at a company with a significant AI infra footprint. Experience with ontology-driven systems or knowledge graphs supporting AI applications. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products , and a core layer delivering intelligent, high-impact experiences directly to our customers . At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives —such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design. This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base. Your Impact ML Platform: Design and operate AppFolio's ML infrastructure on AWS — ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls. Drive AI Cost Discipline: Optimize cost across all AI applications — provider routing, caching, batch vs. real-time, model size selection, and inference economics. Multi-Provider Reliability: Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions. Training & Fine-Tuning Stack: Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation. Productionize Research: Partner with Voice & Agents and Research ML engineers to harden their prototypes into production systems with SLOs, on-call rotations, and observability. AI Safety & Guardrails: Operate AppFolio's AI safety and authorization layer — guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes. Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment. Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you. Sustainability: You value work-life balance as a foundation for sustained high performance. Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems. Must Have ML infra at scale: Has built and operated production ML infrastructure on AWS — ECS, SageMaker, GPUs, autoscaling, and cost controls. Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing. Provider breadth: Direct experience integrating with Google (Vertex / Gemini), OpenAI, and Anthropic APIs in production. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads. RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data. Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience training Small Language Models for production use. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Prior Staff-level role at a company with a significant AI infra footprint. Experience with ontology-driven systems or knowledge graphs supporting AI applications. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products , and a core layer delivering intelligent, high-impact experiences directly to our customers . At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives —such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design. This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base. Your Impact ML Platform: Design and operate AppFolio's ML infrastructure on AWS — ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls. Drive AI Cost Discipline: Optimize cost across all AI applications — provider routing, caching, batch vs. real-time, model size selection, and inference economics. Multi-Provider Reliability: Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions. Training & Fine-Tuning Stack: Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation. Productionize Research: Partner with Voice & Agents and Research ML engineers to harden their prototypes into production systems with SLOs, on-call rotations, and observability. AI Safety & Guardrails: Operate AppFolio's AI safety and authorization layer — guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes. Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment. Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you. Sustainability: You value work-life balance as a foundation for sustained high performance. Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems. Must Have ML infra at scale: Has built and operated production ML infrastructure on AWS — ECS, SageMaker, GPUs, autoscaling, and cost controls. Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing. Provider breadth: Direct experience integrating with Google (Vertex / Gemini), OpenAI, and Anthropic APIs in production. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads. RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data. Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience training Small Language Models for production use. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Prior Staff-level role at a company with a significant AI infra footprint. Experience with ontology-driven systems or knowledge graphs supporting AI applications. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise — working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns — and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products — identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent — shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities — fine-tuning approaches, retrieval strategies, agentic patterns — and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence — defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML — from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands — SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact — and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve — in this case, leasing — and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego — you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems — especially in agentic contexts. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise — working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns — and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products — identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent — shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities — fine-tuning approaches, retrieval strategies, agentic patterns — and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence — defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML — from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands — SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact — and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve — in this case, leasing — and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego — you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems — especially in agentic contexts. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise — working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns — and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products — identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent — shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities — fine-tuning approaches, retrieval strategies, agentic patterns — and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence — defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML — from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands — SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact — and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve — in this case, leasing — and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego — you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems — especially in agentic contexts. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise — working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns — and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products — identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent — shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities — fine-tuning approaches, retrieval strategies, agentic patterns — and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence — defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML — from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands — SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact — and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve — in this case, leasing — and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego — you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems — especially in agentic contexts. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.

AppFolio is more than a company. We’re a community of dreamers, big thinkers, problem solvers, active listeners, and multipliers. At every opportunity, we set the pace while delivering innovation built to carry real estate into the future. One in which every experience feels effortless, yet meaningful. Where customers are empowered to take on any opportunity. We show up as one team, connected by our values to be a force for good. Because together, we have the power to create extraordinary outcomes for our customers, our communities, and ourselves. We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise — working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns — and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products — identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent — shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities — fine-tuning approaches, retrieval strategies, agentic patterns — and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence — defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML — from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands — SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment. Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact — and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve — in this case, leasing — and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego — you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems — especially in agentic contexts. Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline. Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here . About AppFolio AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com . Why AppFolio Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves. Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills. Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities. Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed. Paddle as One. Learn more at appfolio.com/company/careers Statement of Equal Opportunity At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That’s why we’re a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you’re always welcome at AppFolio.