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The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines Work with massive datasets to develop both generic models as well as fine tune models for specific products Build scalable machine learning infrastructure to automate and optimize our ML services Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You’d Have: 2+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in Tensorflow or PyTorch Nice to Haves: Experience deploying software into environments you can't reach from your laptop - on-prem, edge, air-gapped, or otherwise restricted networks. Regulated industries count; the constraint is the point, not the sector. Any prior exposure to government or defense work: military or civilian service, a cleared internship, or time at a federal contractor. Hands-on fine-tuning of open-weight models - LoRA/PEFT, instruction tuning, or training embedding models, at work or on your own. Having written evaluations for a system whose output isn't deterministic: benchmarks, LLM judges, or a regression suite that caught something real. Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery. A shipped project with real users behind it, where you owned it after launch rather than handing it off at merge. 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: $235,200 — $294,000 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.

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams. Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization. Comfortable with light travel (approximately 10%) for customer interaction and team needs. This role will require an active TS security clearance. Ideally You’d Have: 8+ years of experience building and deploying applied ML systems in production environments. Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps. Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation. Hands-on experience with retrieval systems, embeddings, or representation learning. Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end. Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production. Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity. Nice to Haves: Experience deploying ML systems into air-gapped, classified, or otherwise disconnected environments - customer data centers, on-prem infrastructure, or networks with no path to a cloud provider. Prior work with DoD, the intelligence community, or federal mission users - including the judgment to learn a mission well enough to know what "correct" means for the operator using your system. Hands-on experience with geospatial data or GEOINT: reasoning over maps, imagery, or spatial reference systems. Depth in model adaptation - training or fine-tuning embedding models, instruction tuning, LoRA/PEFT, or RLHF. Experience building evaluation infrastructure for non-deterministic systems: LLM-as-judge, regression suites for agent behavior, or drift detection in production. A track record of turning a forward-deployed prototype into a supported, documented capability other engineers can deploy without you. 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: $274,400 — $343,000 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.

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams. Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization. Comfortable with light travel (approximately 10%) for customer interaction and team needs. This role will require an active TS security clearance. Ideally You’d Have: 8+ years of experience building and deploying applied ML systems in production environments. Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps. Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation. Hands-on experience with retrieval systems, embeddings, or representation learning. Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end. Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production. Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity. Nice to Haves: Experience deploying ML systems into air-gapped, classified, or otherwise disconnected environments - customer data centers, on-prem infrastructure, or networks with no path to a cloud provider. Prior work with DoD, the intelligence community, or federal mission users - including the judgment to learn a mission well enough to know what "correct" means for the operator using your system. Hands-on experience with geospatial data or GEOINT: reasoning over maps, imagery, or spatial reference systems. Depth in model adaptation - training or fine-tuning embedding models, instruction tuning, LoRA/PEFT, or RLHF. Experience building evaluation infrastructure for non-deterministic systems: LLM-as-judge, regression suites for agent behavior, or drift detection in production. A track record of turning a forward-deployed prototype into a supported, documented capability other engineers can deploy without you. 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: $274,400 — $343,000 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.

The Role: Scale AI is hiring a highly skilled foundational IT Systems Engineer for our Public Sector IT team to design, build, and operate secure, scalable infrastructure that empowers employees to do their best work. You’ll join a creative, fast-moving, solutions-oriented group that architects and implements automation across identity and access management, endpoint management, and our broader SaaS stack. Leveraging Okta Workflows, GCC High/Azure Gov, and your familiarity with federal frameworks (FedRAMP High, IL6, CMMC), you’ll deliver robust, audit-ready systems that meet stringent compliance requirements. The ideal candidate pairs deep IAM best practices and hands-on SaaS administration with a zero-trust mindset, clear documentation, and a genuine drive to make people happy—while protecting system integrity in a fast-paced, high-security environment. You will: Assist with the administration of our tech stack with platforms such as Okta, GCC High, Opal, Slack, Jamf, Jira, and many more Provide escalated assistance to the IT Services and Support team Partner with Security/Compliance on audit artifacts (SSP updates, POA&Ms, control mappings to NIST 800-53/171, CMMC 2.0). Create and update technology documentation for internal IT teams and Scale employees Design and maintain Zero-Trust controls (device posture, network segmentation, Conditional Access) across GCC High/Azure Gov and Okta. Build Okta Workflows and lightweight services (webhooks/queues) to automate joiner–mover–leaver events, access reviews, and deprovisioning. Own change management for IT systems in regulated environments (CAB records, rollback plans, validation evidence). Ideally you'd have: 5+ years of IT systems, infrastructure, and/or engineering experience Experience with integrating with SaaS APIs and SDKs Experience with leveraging Okta or similar identity management systems for authentication and provisioning methods such as SAML, OIDC, and SCIM Scripting experience with Python, Powershell, and/or bash Experience working within SCIFs Familiarity with IL6 / FedRAMP High / CMMC 2.0 control families and how they translate to concrete IT configs Nice to haves: IT Security and Compliance focused mindset Familiarity with Infrastructure-as-Code for identity/MDM configs (e.g., Terraform providers for Okta/Jamf/Azure) Possession of an active Secret or TS/SCI clearance 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: $148,800 — $186,000 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.

The goal of a Senior Machine Learning Engineer at Scale is to own how we apply generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production. Our senior machine learning engineers are handed problems that don't yet have an established approach, they propose the architecture, build it with support from other engineers, and are accountable for whether it holds up in the environments our customers depend on. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with our primary focus on agentic systems built on large language models. We are developing agents that solve complex operational and planning challenges for government partners: agent frameworks that integrate custom retrieval pipelines and production APIs, memory and context-management systems that hold state across long-running tasks, geospatial reasoning over maps and spatial data, and the evaluation tooling that benchmarks and refines agent behavior. We also apply reinforcement learning in targeted places where it earns its keep, and our computer vision work advances evaluation, labeling efficiency, and multimodal model training in support of defense applications. As a Senior MLE, you'll have design authority over a capability area - the final say on the patterns used within your team, and the responsibility to make those patterns work under real constraints: classified environments, limited compute, and correctness requirements that don't bend. You will: Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them Take state of the art models developed internally and from the community and put them into production to solve problems for our customers and taskers Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines Build scalable machine learning infrastructure to automate and optimize our ML services Work directly with government users and subject-matter experts, and translate what you learn into technical direction Act as a force multiplier and a primary reviewer for your team, mentoring at least one engineer, and your manager's go-to on feasibility questions Communicate technical tradeoffs clearly to non-technical stakeholders Treat security and compliance as design constraints to engineer around rather than blockers to route past Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You'd Have: 5+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in PyTorch or Tensorflow Experience mentoring or reviewing the work of other engineers Nice to Haves: Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments Experience with computer vision, generative AI models, large language models, or agentic systems Familiarity with ML evaluation frameworks and agentic model design Experience deploying ML in classified, air-gapped, or IL5+ environments Geospatial or GEOINT experience Inference optimization experience Fine-tuning experience: SFT, RL, or embedding models 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: $235,200 — $294,000 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.

The goal of a Senior Machine Learning Engineer at Scale is to own how we apply generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production. Our senior machine learning engineers are handed problems that don't yet have an established approach, they propose the architecture, build it with support from other engineers, and are accountable for whether it holds up in the environments our customers depend on. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with our primary focus on agentic systems built on large language models. We are developing agents that solve complex operational and planning challenges for government partners: agent frameworks that integrate custom retrieval pipelines and production APIs, memory and context-management systems that hold state across long-running tasks, geospatial reasoning over maps and spatial data, and the evaluation tooling that benchmarks and refines agent behavior. We also apply reinforcement learning in targeted places where it earns its keep, and our computer vision work advances evaluation, labeling efficiency, and multimodal model training in support of defense applications. As a Senior MLE, you'll have design authority over a capability area - the final say on the patterns used within your team, and the responsibility to make those patterns work under real constraints: classified environments, limited compute, and correctness requirements that don't bend. You will: Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them Take state of the art models developed internally and from the community and put them into production to solve problems for our customers and taskers Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines Build scalable machine learning infrastructure to automate and optimize our ML services Work directly with government users and subject-matter experts, and translate what you learn into technical direction Act as a force multiplier and a primary reviewer for your team, mentoring at least one engineer, and your manager's go-to on feasibility questions Communicate technical tradeoffs clearly to non-technical stakeholders Treat security and compliance as design constraints to engineer around rather than blockers to route past Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You'd Have: 5+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in PyTorch or Tensorflow Experience mentoring or reviewing the work of other engineers Nice to Haves: Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments Experience with computer vision, generative AI models, large language models, or agentic systems Familiarity with ML evaluation frameworks and agentic model design Experience deploying ML in classified, air-gapped, or IL5+ environments Geospatial or GEOINT experience Inference optimization experience Fine-tuning experience: SFT, RL, or embedding models 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: $235,200 — $294,000 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.

The goal of a Senior Machine Learning Engineer at Scale is to own how we apply generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production. Our senior machine learning engineers are handed problems that don't yet have an established approach, they propose the architecture, build it with support from other engineers, and are accountable for whether it holds up in the environments our customers depend on. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with our primary focus on agentic systems built on large language models. We are developing agents that solve complex operational and planning challenges for government partners: agent frameworks that integrate custom retrieval pipelines and production APIs, memory and context-management systems that hold state across long-running tasks, geospatial reasoning over maps and spatial data, and the evaluation tooling that benchmarks and refines agent behavior. We also apply reinforcement learning in targeted places where it earns its keep, and our computer vision work advances evaluation, labeling efficiency, and multimodal model training in support of defense applications. As a Senior MLE, you'll have design authority over a capability area - the final say on the patterns used within your team, and the responsibility to make those patterns work under real constraints: classified environments, limited compute, and correctness requirements that don't bend. You will: Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them Take state of the art models developed internally and from the community and put them into production to solve problems for our customers and taskers Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines Build scalable machine learning infrastructure to automate and optimize our ML services Work directly with government users and subject-matter experts, and translate what you learn into technical direction Act as a force multiplier and a primary reviewer for your team, mentoring at least one engineer, and your manager's go-to on feasibility questions Communicate technical tradeoffs clearly to non-technical stakeholders Treat security and compliance as design constraints to engineer around rather than blockers to route past Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You'd Have: 5+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in PyTorch or Tensorflow Experience mentoring or reviewing the work of other engineers Nice to Haves: Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments Experience with computer vision, generative AI models, large language models, or agentic systems Familiarity with ML evaluation frameworks and agentic model design Experience deploying ML in classified, air-gapped, or IL5+ environments Geospatial or GEOINT experience Inference optimization experience Fine-tuning experience: SFT, RL, or embedding models 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: $235,200 — $294,000 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.

We are seeking a highly technical Infrastructure Security Engineer to join our Public Sector Infrastructure & Security team. Our Infrastructure Security Engineers ensure the security and integrity of our platform. You will be responsible for securing large cloud environments, orchestrating and securing various compute clusters, and reviewing infrastructure as code. Your expertise in cloud security, infrastructure automation, and advanced security practices will be essential in maintaining and enhancing our security posture. You will: Secure infrastructure across large cloud hosting providers (e.g., AWS, Azure, GCP). Implement and maintain robust security configurations and policies for cloud environments. Conduct regular security assessments and audits of infrastructure to identify vulnerabilities and areas for improvement. Develop and enforce security best practices for infrastructure automation and orchestration. Collaborate with DeveloperExperience, IT, and product teams to integrate security into all stages of the infrastructure lifecycle. Review and secure infrastructure as code (e.g., Terraform, CloudFormation). Educate and mentor team members on infrastructure security best practices and emerging threats. Must have: At least an active Top Secret clearance. This is a requirement and candidates will not be considered who do not hold at least a Top Secret clearance. Ideally, you’d have: Proven experience as a Security Engineer with a focus on infrastructure security. Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes. Strong understanding of modern Javascript application design. Production experience with Kubernetes backed services Hands-on experience with SAST and DAST tools and methodologies. Familiarity with terraform orchestration for infrastructure management. You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input. Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders. Demonstrated ability to influence security strategies and drive improvements within a team. Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus. 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: $198,400 — $342,000 USD The base salary range for this full-time position in the locations of Hawaii, Washington DC, Texas, Colorado is: $178,400 — $307,000 USD The base salary range for this full-time position in the location of St. Louis is: $148,800 — $256,000 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.