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Careers at Scaleai

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scale.comHQ: San Francisco, California, United States

Trusted by world class companies, Scale delivers high quality training data for AI applications such as self-driving cars, mapping, AR/VR, robotics, and more.

Sector:computer software

All Openings (83)

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About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and to set the AI/ML technical direction across AIS — the methods, architectures, and standards other teams build on, not just your own workstream. This is a hands-on research and engineering role at staff scope: you’ll write code — training pipelines, evaluation systems, infrastructure, or whatever the problem calls for — and ship production systems yourself, while also setting AIML technical direction and raising the bar for engineers and scientists across AIS. You will: Move across AIS’s core problem areas as needed — training/fine-tuning, inference, memory and retrieval, evaluation and observability, orchestration and tool-use infrastructure, applied research on new agent capabilities — going wherever the technical leverage is highest rather than owning one fixed surface Research and prototype novel methods for agent performance improvement in a production/enterprise-ready setting — continuous learning loops, automated curriculum or data generation from production traces, online or offline RL — and validate them with rigorous experiments before they ship, making the call on where to build new infrastructure versus apply existing methods Build AI agents and internal tooling that reduce bottlenecks in AIS’s own processes — cutting down time spent on repetitive evaluation, data, or experimentation work so teams can focus on the hard problems Partner with other ML engineers, software engineers, product managers, customers, data annotators, and Forward Deployed Engineers to take your work from idea to production and translate enterprise and government requirements into robust ML capabilities Set AI/ML technical direction, mentor senior and staff-track engineers and scientists across teams, and raise the bar on experimental rigor org-wide Requirements: 5+ years of experience as an ML engineer or applied/research scientist, including direct experience training or fine-tuning models in production systems PhD in Computer Science, Electrical Engineering, or a related field Broad, hands-on fluency across the agentic ML stack — model training and fine-tuning (SFT, RLHF/RLAIF, reward modeling), evaluation and observability infrastructure, and agent architecture (tool use, planning, memory, multi-agent orchestration) — with demonstrated depth or expertise in at least one area within the AI/ML domain Demonstrated ability to move across problem areas rather than specialize in one corner of the ML stack — comfortable picking up unfamiliar parts of a system quickly Track record of partnering with software engineers to productionize research and experimental work, not just deliver a one-off analysis — and of pushing code to production yourself when needed — with a genuine drive for pathfinding, 0-to-1 problems where the right approach isn’t yet known Track record of setting AI/ML technical direction — choosing methods and architectures that other teams adopt — and collaborating across functions (Product, Forward Deployed Engineering, etc.) to navigate ambiguous requirements and bring them to production Track record of mentoring engineers and scientists, giving and receiving direct, substantive technical feedback at a staff level, and influencing decisions and standards beyond your own team — through design reviews, technical writing, or shaping how other teams approach a problem Nice to have: Published research, open-source contributions, or patents in agent training methods, LLM alignment, or applied ML Experience with online learning, continuous fine-tuning, or automated data/curriculum generation from production traces Experience with model or systems optimization (e.g., training efficiency, latency, cost, or inference efficiency at scale) Experience working in regulated or enterprise/government contexts Track record of taking a novel training method or agent architecture from prototype to something running reliably in production, navigating ambiguity along the way Prior experience as a technical lead setting direction across multiple teams or problem areas Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $250,000 — $350,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI / ML & Data ScienceVia Greenhouse
Verified19 days ago

Staff/Senior Machine Learning Research Engineer, Intelligent Systems

On-sitefull timeLead / StaffSan Francisco, United States
Apply Now

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and to set the AI/ML technical direction across AIS — the methods, architectures, and standards other teams build on, not just your own workstream. This is a hands-on research and engineering role at staff scope: you’ll write code — training pipelines, evaluation systems, infrastructure, or whatever the problem calls for — and ship production systems yourself, while also setting AIML technical direction and raising the bar for engineers and scientists across AIS. You will: Move across AIS’s core problem areas as needed — training/fine-tuning, inference, memory and retrieval, evaluation and observability, orchestration and tool-use infrastructure, applied research on new agent capabilities — going wherever the technical leverage is highest rather than owning one fixed surface Research and prototype novel methods for agent performance improvement in a production/enterprise-ready setting — continuous learning loops, automated curriculum or data generation from production traces, online or offline RL — and validate them with rigorous experiments before they ship, making the call on where to build new infrastructure versus apply existing methods Build AI agents and internal tooling that reduce bottlenecks in AIS’s own processes — cutting down time spent on repetitive evaluation, data, or experimentation work so teams can focus on the hard problems Partner with other ML engineers, software engineers, product managers, customers, data annotators, and Forward Deployed Engineers to take your work from idea to production and translate enterprise and government requirements into robust ML capabilities Set AI/ML technical direction, mentor senior and staff-track engineers and scientists across teams, and raise the bar on experimental rigor org-wide Requirements: 5+ years of experience as an ML engineer or applied/research scientist, including direct experience training or fine-tuning models in production systems PhD in Computer Science, Electrical Engineering, or a related field Broad, hands-on fluency across the agentic ML stack — model training and fine-tuning (SFT, RLHF/RLAIF, reward modeling), evaluation and observability infrastructure, and agent architecture (tool use, planning, memory, multi-agent orchestration) — with demonstrated depth or expertise in at least one area within the AI/ML domain Demonstrated ability to move across problem areas rather than specialize in one corner of the ML stack — comfortable picking up unfamiliar parts of a system quickly Track record of partnering with software engineers to productionize research and experimental work, not just deliver a one-off analysis — and of pushing code to production yourself when needed — with a genuine drive for pathfinding, 0-to-1 problems where the right approach isn’t yet known Track record of setting AI/ML technical direction — choosing methods and architectures that other teams adopt — and collaborating across functions (Product, Forward Deployed Engineering, etc.) to navigate ambiguous requirements and bring them to production Track record of mentoring engineers and scientists, giving and receiving direct, substantive technical feedback at a staff level, and influencing decisions and standards beyond your own team — through design reviews, technical writing, or shaping how other teams approach a problem Nice to have: Published research, open-source contributions, or patents in agent training methods, LLM alignment, or applied ML Experience with online learning, continuous fine-tuning, or automated data/curriculum generation from production traces Experience with model or systems optimization (e.g., training efficiency, latency, cost, or inference efficiency at scale) Experience working in regulated or enterprise/government contexts Track record of taking a novel training method or agent architecture from prototype to something running reliably in production, navigating ambiguity along the way Prior experience as a technical lead setting direction across multiple teams or problem areas Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $250,000 — $350,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI / ML & Data ScienceVia Greenhouse
Verified19 days ago

Engineering Manager, Frontier AI Infrastructure - Public Sector

On-sitefull timeMid-LevelWashington, United States
Apply Now

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are seeking a hands-on Engineering Manager to lead our Frontier AI Infrastructure team within Public Sector Engineering. This is a 50/50 role : you'll spend roughly half your time writing and reviewing code, and half your time leading, coaching, and growing a small team of engineers. Your team owns the model inference layer — enabling state-of-the-art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You'll lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and debug platform issues, and you'll partner upstream with Product to catch issues before they break, moving the team from "infra-only debugging" to proactive integration testing. You will: As a manager - 50/50 management and hands on coding experience. Lead, coach, and grow a team of engineers — own hiring, onboarding, performance, and career development. Set technical direction and quarterly priorities for the inference layer, and hold the team accountable to delivery on customer and contract commitments. Run the operational rhythm of the team: sprint planning, on-call rotation, incident review, and postmortems. Partner with Product, Program, and Deployed Engineering leadership to translate customer and mission requirements into roadmap. Represent the team in customer engagements and vendor escalations, including with government stakeholders. Design and implement secure, scalable backend systems for Public Sector customers, leveraging Scale's modern cloud-native AI infrastructure. Own services and systems alongside your team, define their long-term health goals, and improve the health of surrounding components. Stay in the code: review PRs, debug production issues, and take on meaningful technical work yourself. Must have: At least 1-2+ years of direct people management experience leading a team of software engineers (hiring, performance management, and career development), plus a strong track record as a hands-on individual contributor. At least an active Secret clearance , and the ability and willingness to up-level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a Secret clearance. Willingness to remain hands-on in the code — this is not a purely people-leadership role. Ideally you'd have: Full Stack Development: Proficiency in both front-end and back-end development, including modern web frameworks, programming languages, and databases. Experience developing and delivering software to air-gapped and isolated environments is a plus. Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and orchestration (e.g., Kubernetes). Familiarity with cloud platforms (AWS, Azure, GCP) and experience developing and deploying applications in cloud-native environments. Security Focused: Experience with federal compliance frameworks and requirements (e.g., Cloud SRG, FedRAMP, STIG Benchmarks). Experience delivering software and technical solutions that meet strict security and regulatory requirements. Team Building: Experience building or scaling a team from a small size, and setting engineering standards (code review, testing, on-call) that stick. Problem Solving: Strong analytical skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to technical obstacles. Collaboration and Communication: Excellent interpersonal and communication skills to collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences. Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving requirements in a fast-moving AI landscape. Must be able to support work 3–4 days a week from the DC office. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of Washington DC is: $213,600 — $267,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Engineering ManagementVia Greenhouse
Verified20 days ago

Software Engineer, Platform

On-sitefull timeSeniorLondon, United Kingdom
Apply Now

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the SGP Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design and implementation of our foundational platforms and systems that will become the baseline for Scale’s capabilities. Collaborate with cross-functional teams to define and understand requirements, design, and deliver new features within a highly iterative and innovative software development lifecycle. Work within the team to lead the market in your team’s AI domain through experimentation with the latest techniques and technologies in this area. Proactively identify opportunities for and drive improvements to current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing guidance and insights on development processes and technologies. Ideally you’d have: 5+ years of full-time engineering experience, post-graduation, with specialties in back-end systems. Excitement to work with AI technologies and build agentic experiences. Extensive experience in software development and a deep understanding of highly scalable and reliable distributed systems hosted on public cloud platforms. Experience building document retrieval and understanding systems, such as RAG, to accurately ingest large-scale client knowledge into client agents and applications. A strong track record of independently owning and delivering successful engineering projects, including the ability to collaborate with and inspire others to engage with the problem space. Excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders. Experience working fluently with standard containerization and deployment technologies like Kubernetes, Terraform, Docker, etc. Experience with long-running agent/code orchestration platforms, such as Temporal. Mastery of storing state with structured databases, including Postgres. Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, GHA). Nice to haves: Experience across multiple cloud platforms (GCP, AWS, Azure, Oracle, on-premise). Experience with multiple ways to persist contextual data, e.g., knowledge graphs and hierarchical indexes. Experience with other types of large data solutions, e.g., Databricks and Snowflake. Experience with authentication/authorization systems (Zanzibar, Authz, etc.). Experience scaling technical products at hyper-growth startups. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Software EngineeringVia Greenhouse
Verified20 days ago

GenAI Compliance Operations & Programs Associate

On-sitefull timeEntry / JuniorMexico City, Mexico
Apply Now

About the Role This role will serve as a key execution partner to the GenAI Customer Compliance Manager, with a strong focus on supporting GenAI delivery workflows through embedded compliance operations and Legal coordination. The GenAI Compliance Operations & Programs Associate will sit at the intersection of Delivery, Ops, and Legal, ensuring that compliance considerations are integrated early in the project lifecycle, risks are clearly identified and prioritized, and Legal is engaged with the right context at the right time. By owning execution, coordination, and delivery integration, this role frees the Customer Compliance Manager to focus on strategy, governance, and risk frameworks. The role requires strong operational ownership, comfort with ambiguity, and the ability to drive alignment across fast-moving, cross-functional teams. Key Responsibilities Compliance Review Operations & Legal Coordination Manage end-to-end compliance review workflows for GenAI projects — from early-stage intake through review, approval, launch, and verification — in close partnership with Engagement Management and Delivery. Evaluate incoming work for compliance risk signals (e.g., data sensitivity, copyright exposure, privacy concerns); triage and prioritize requests for Legal based on risk, scope, and delivery timelines. Partner with Engagement Management to translate and execute risk mitigation at both the project and customer level, gather operational input to develop and prioritize systematic compliance controls, and train/educate Ops stakeholders on common or emerging compliance risks. Ensure Legal receives clear, structured, and actionable context; coordinate reviewers across Legal and internal teams to support SLA adherence. Identify workflow friction points and contribute to improving processes, templates, and prioritization frameworks. Maintain dashboards to track throughput, bottlenecks, SLAs, and risk trends. Risk Mitigation Solutions & Monitoring Support Engineering and Ops in developing and implementing scalable risk mitigation solutions. Operationalize solutions into repeatable workflows aligned with delivery processes. Monitor adoption and effectiveness; escalate gaps or risks as needed. Customer Audit Support Support audit readiness activities including evidence collection and documentation under the direction of the Customer Compliance Manager. Assist in preparing audit packages and tracking progress toward readiness milestones. Support audit remediation efforts and follow-through. Access Control & Operational Hygiene Manage day-to-day access governance across systems and sensitive datasets (including Redash and internal/external Google Groups). Execute quarterly access reviews and cleanup processes in alignment with policies set by the Customer Compliance Manager. Enforce and standardize permissions and operational controls; flag anomalies for escalation. Qualifications Required 1-3 years of experience in operations, program management, compliance, or GenAI/technical delivery environments. Must be local to Mexico with advanced English speaking skills Bachelor’s degree required; preferred fields include Business Administration, Operations Management, Information Systems, or Public Policy. Direct experience supporting or operating within GenAI/AI delivery workflows strongly preferred. Working knowledge of basic legal/compliance concepts (privacy, copyright, data handling). Proven ability to triage, prioritize, and manage high-volume workflows. Strong cross-functional collaboration skills, especially with Legal, Ops, Product, and Engineering. Experience with data tools and dashboards (e.g., Redash or similar). Basic understanding of SQL (e.g., able to build and run basic queries) High attention to detail and strong operational follow-through. Nice to Have Experience in GenAI, Trust & Safety, or data compliance environments. Familiarity with legal intake processes or working directly with Legal teams. Experience designing operational workflows, intake systems, or triage frameworks. Exposure to risk assessment or prioritization models. Background in Law, Data Science, or Computer Science. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI / ML & Data ScienceVia Greenhouse
Verified21 days ago

Software Engineering Intern

On-siteinternshipInternshipSan Francisco, United States
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At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Francisco Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to customers, figuring out 'what' to build and then iterating Previous Computer Science/Software Engineering internship experience Track record of shipping high-quality products and features Experience building systems that process large volumes of data Experience with Python, Typescript, React, and/or MongoDB Nice to Have Hands-on experience with LLMs, evaluations, or agentic systems — whether from coursework, research, or personal projects Open source contributions or a portfolio of shipped side projects How We Work Our credos shape how we make decisions and work as a team: Earn Customer Love — trust is earned with every interaction, every delivery, and every problem we solve Team Flow — ideas, energy, and support move freely across teams; optimize for the whole Quality is Our Cheat Code — the systems that deliver quality consistently are a structural advantage Find the 20% — find the inputs that drive the outcomes and execute them completely Write the Market — our research puts us at the frontier, and we bring our partners there first Three Moves Ahead — consider the consequences of consequences, and plan accordingly PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Software EngineeringVia Greenhouse
Verified24 days ago

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the US. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI / ML & Data ScienceVia Greenhouse
Verified24 days ago

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the country they reside in. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

View more...
AI / ML & Data ScienceVia Greenhouse
Verified24 days ago

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the country they reside in. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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AI / ML & Data ScienceVia Greenhouse
Verified24 days ago

Software Engineer - New Grad

On-sitefull timeEntry / JuniorSan Francisco, United States
Apply Now

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Every industry is moving AI to the center of operations, but there is still no clear blueprint for getting from pilot to profit. That is the problem our engineers work on. As a New Grad Software Engineer, you will own meaningful, customer-facing work from day one — shipping products, talking directly to the customers who use them, and iterating fast. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Build a customer service RAG application that handles thousands of questions a day Integrate a cutting-edge ML model that predicts churn into a customer's retention system Requirements A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to customers, figuring out 'what' to build and then iterating Previous Product/Software Engineering internship experience Track record of shipping high-quality products and features at scale Experience building systems that process large volumes of data Experience with Python, Typescript, React, and/or MongoDB Nice to Have Hands-on experience with LLMs, evaluations, or agentic systems — whether from internships, research, or personal projects Open source contributions or a portfolio of shipped side projects How We Work Our credos shape how we make decisions and work as a team: Earn Customer Love — trust is earned with every interaction, every delivery, and every problem we solve Team Flow — ideas, energy, and support move freely across teams; optimize for the whole Quality is Our Cheat Code — the systems that deliver quality consistently are a structural advantage Find the 20% — find the inputs that drive the outcomes and execute them completely Write the Market — our research puts us at the frontier, and we bring our partners there first Three Moves Ahead — consider the consequences of consequences, and plan accordingly Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $124,000 — $162,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

View more...
Software EngineeringVia Greenhouse
Verified25 days ago

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