Scaleai

<h2>About the Program</h2>
The Human Frontier Collective (HFC) brings researchers and scientists together to tackle consequential problems in AI. In partnership with Scale Labs, we are building a small cohort of researchers to work on the empirical foundations of AI safety.
That work includes finding where models fail, checking whether safety controls hold up under pressure in realistic settings, and studying how AI agents (mis-)behave over long-horizon tasks. Scholars take open research questions like these and turn them into work that improves how frontier AI systems are evaluated and safeguarded.
Each scholar owns a substantial part of a safety research project. You'll work alongside a mentor from the research question through the experiments to deciding what to test next.
<h2>Research Areas</h2>
Mentors will guide Research Scholars on projects in selected AI safety research areas in select AI safety research areas, such as:
<ul>
<li>AI control and chain-of-thought monitoring: Developing techniques to oversee and constrain AIs, including detecting harmful intent or deception.</li>
<li>Alignment auditing and evaluations: Building scalable methods to test whether models have hidden goals, misaligned behaviors or unsafe tendencies.</li>
<li>Multi-agent safety: Studying the risks that emerge when multiple agents interact, such as collusion, coordinated failures, or unexpected collective behavior.</li>
<li>Recursive Self-Improvement (RSI) safety: Investigating how to keep AI systems safe and aligned as AIs increasingly contribute to their own development.</li>
<li>Science of Evaluations: examining when and how models recognize they're being tested, and how situational awareness affects the reliability/validity of evaluations.</li>
<li>Misuse risks and evaluations: Developing methods to assess how AI systems could be exploited by malicious actors, including evaluating their potential to enable harmful activities.</li>
</ul>
Projects are matched to demonstrated expertise; we don’t expect any candidate to cover every area.
<h2>Representative Research</h2>
<ul>
<li><a href="https://labs.scale.com/papers/aspi" rel="noopener noreferrer ugc" target="_blank">ASPI</a>: 728 task–attack scenarios testing how clarification-seeking changes prompt-injection vulnerability in LLM agents.</li>
<li><a href="https://labs.scale.com/papers/propensitybench" rel="noopener noreferrer ugc" target="_blank">PropensityBench</a>: simulating real-world pressure to choose between safe or harmful behavior</li>
<li><a href="https://labs.scale.com/papers/bioriskeval" rel="noopener noreferrer ugc" target="_blank">BioRiskEval</a>: evaluating whether safeguards for open-weight bio-foundation models remain robust under fine-tuning and probing.</li>
<li>See more work from the <a href="https://hfc.scale.com/research" rel="noopener noreferrer ugc" target="_blank">Human Frontier Collective</a>.</li>
</ul>
<h2>What You'll Do</h2>
Projects are mentor-guided. By default, you will be given a list of research proposals and match you with one based on your research interests and background. You’ll meet weekly with a Scale researcher who sets the direction and gives feedback, and you will drive the day-to-day work.
<ul>
<li>Own research end to end: Turn a high-level safety question into hypotheses, baselines, and controlled experiments, and produce work that others can inspect and build on.</li>
<li>Build the measurement: Implement and debug evaluation harnesses, agent environments, datasets, monitoring methods, or post-training experiments.</li>
<li>Exercise research judgment: Identify confounds, separate what a model can do from what it tends to do, make sense of negative results, and decide what to try next without step-by-step direction.</li>
<li>Make the work legible: Produce reproducible code, experiment logs, analysis, and precise technical writing. External outputs, where appropriate, remain subject to research, security, and communications review. Outputs also include research papers, which will be submitted to top ML conferences (NeurIPS, ICML, ICLR).</li>
</ul>
<h2>Who We're Looking For</h2>
You may be a good fit if you:
<ul>
<li>are motivated by reducing catastrophic risks from advanced AI systems;</li>
<li>are interested in technical safety research, such as alignment evaluations, AI control, monitoring, multi-agent safety, or open-weight model safety;</li>
<li>are pursuing or have completed a PhD in CS, ML, statistics, mathematics, or a related field (we also encourage researchers with an equivalent track record to apply);</li>
<li>can make progress with high-level guidance, including implementing, debugging, getting unstuck, interpreting results, and proposing next experiments;</li>
<li>communicate research clearly and handle confidential information and internal systems responsibly.</li>
</ul>
<h2>Application Process</h2>
<ul>
<li>Apply: Submit your resume or CV, your Google Scholar profile if you have one, and one research project you substantially owned, with 2–3 sentences on your contribution.</li>
<li>Research background discussion: Walk us through a past project, including what you tried, what didn't work, and what you learned.</li>
<li>Research design: Work through a research problem with us and propose how you'd approach it.</li>
<li>Onboarding: Successful candidates complete the applicable recruiting, work-authorization, security, and project-onboarding steps.</li>
</ul><div>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 &amp; 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 <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf" rel="noopener noreferrer ugc" target="_blank">Know Your Rights poster</a> 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 <a href="https://scale.com/legal/privacy" target="_blank" rel="noopener noreferrer ugc">privacy policy</a> for additional information.</div>

Safety Research Scholar - Human Frontier Labs

Scale is building reliable AI systems for the world’s most important decisions. Our products help leading enterprises, governments, and frontier AI labs build, deploy, and evaluate AI systems at scale.
The Orchestration Platform is a core technology used across the company to run durable, reliable, and scalable workflows. It powers the complex, long-running processes behind Scale’s products - from data and model-evaluation pipelines to operational systems and customer-facing workflows.
As a Senior Software Engineer, you will help build and evolve this foundational orchestration platform. You will design the primitives, services, and developer experience that enable teams across Scale to author, operate, observe, and safely scale distributed workflows. This is a high-leverage role for an engineer excited by distributed systems, reliability, and platform infrastructure used by many internal teams.
You will:
<ul>
<li>Lead the architecture, design, implementation, and operation of Scale’s core orchestration platform.</li>
<li>Build durable workflow infrastructure using technologies such as Temporal, Cadence, Kubernetes, and cloud-native systems.</li>
<li>Define platform primitives and APIs for scheduling, retries, state management, task execution, observability, and workflow lifecycle management.</li>
<li>Partner with product, infrastructure, data, and application teams to understand workflow needs and turn them into reusable platform capabilities.</li>
<li>Improve the reliability, scalability, security, and developer experience of services that run critical company workflows.</li>
<li>Establish technical standards and best practices for distributed workflow development, deployment, testing, and incident response.</li>
<li>Drive cross-functional technical decisions and communicate platform direction clearly to engineers and stakeholders.</li>
</ul>
Ideally, you have:
<ul>
<li>5+ years of full-time software engineering experience, with a focus on backend, infrastructure, and distributed systems.</li>
<li>Experience building and operating production systems with strong requirements for reliability, availability, and scale.</li>
<li>Deep familiarity with workflow orchestration platforms such as Temporal, Cadence, AWS Step Functions, Kubernetes, or similar systems.</li>
<li>Deep familiarity with Kubernetes and containerized production environments, and familiarity with Terraform, Docker.</li>
<li>Strong knowledge of distributed-systems concepts, including asynchronous execution, retries, idempotency, fault tolerance, state management, and observability.</li>
<li>A track record of leading technically complex projects from design through rollout and ongoing operation.</li>
<li>Excellent communication skills and the ability to collaborate effectively with platform consumers and non-technical stakeholders.</li>
</ul>
Nices to haves:
<ul>
<li>Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).</li>
<li>Experience with authentication/authorization systems (Zanzibar, Authz, etc.)</li>
<li>Experience scaling products at hyper-growth startups.</li>
<li>Excitement to work with AI technologies.</li>
</ul><div><div><div>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.</div><div>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:</div><div>$216,000—$270,000 USD</div></div></div><div>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 &amp; 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 <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf" rel="noopener noreferrer ugc" target="_blank">Know Your Rights poster</a> 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 <a href="https://scale.com/legal/privacy" target="_blank" rel="noopener noreferrer ugc">privacy policy</a> for additional information.</div>

Senior Software Engineer, Orchestration Platform

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 &amp; Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.
Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast.
<h2>Example Projects</h2>
<ul>
<li>Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments</li>
<li>Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets</li>
<li>Build orchestration for fleets of asynchronous agents running long-horizon tasks</li>
<li>Develop systems that automatically alert users to deviations and anomalies in incoming data</li>
<li>Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output</li>
<li>Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents</li>
<li>Build evaluation infrastructure that measures model reliability against mission requirements</li>
<li>Ship full-stack tooling that lets analysts query, visualize, and explore mission data</li>
<li>Deploy and harden applications into secure, air-gapped, and cloud-native government environments</li>
</ul>
<h2>Requirements</h2>
<ul>
<li>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)</li>
<li>Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to users, figuring out 'what' to build and then iterating</li>
<li>Previous Product/Software Engineering internship experience</li>
<li>Track record of shipping high-quality products and features at scale</li>
<li>Experience building systems that process large volumes of data</li>
<li>Experience with Python, Typescript, React, and/or MongoDB</li>
<li>Strong written and verbal communication — you will work directly with government stakeholders and must be able to explain technical concepts to non-technical audiences</li>
<li>Comfort with ambiguity and evolving requirements, and a willingness to learn new domains quickly</li>
</ul>
<h2>Nice to Have</h2>
<ul>
<li>Hands-on experience with LLMs, evaluations, or agentic systems — whether from internships, research, or personal projects</li>
<li>Familiarity with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes)</li>
<li>Exposure to ETL, data modeling, data warehousing, or data governance</li>
<li>Prior experience with, or demonstrated interest in, national security, defense, or civil government technology</li>
<li>Open source contributions or a portfolio of shipped side projects</li>
</ul>
<h2>How We Work</h2>
Our credos shape how we make decisions and work as a team:
<ul>
<li>Earn Customer Love — trust is earned with every interaction, every delivery, and every problem we solve</li>
<li>Team Flow — ideas, energy, and support move freely across teams; optimize for the whole</li>
<li>Quality is Our Cheat Code — the systems that deliver quality consistently are a structural advantage</li>
<li>Find the 20% — find the inputs that drive the outcomes and execute them completely</li>
<li>Write the Market — our research puts us at the frontier, and we bring our partners there first</li>
<li>Three Moves Ahead — consider the consequences of consequences, and plan accordingly</li>
</ul><div><div><div>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.</div><div>The base salary range for this full-time position in the location of San Francisco is:</div><div>$124,000—$162,000 USD</div></div></div><div>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 &amp; 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 <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf" rel="noopener noreferrer ugc" target="_blank">Know Your Rights poster</a> 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 <a href="https://scale.com/legal/privacy" target="_blank" rel="noopener noreferrer ugc">privacy policy</a> for additional information.</div>

Software Engineer, Public Sector - New Grad

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 <a href="https://scale.com/blog/meet-the-legend-behind-the-name-scale-donovan" rel="noopener noreferrer ugc" target="_blank">Donovan</a> and <a href="https://scale.com/blog/thunderforge-ai-for-american-defense" rel="noopener noreferrer ugc" target="_blank">Thunderforge</a>, 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:
<ul>
<li>Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability.</li>
<li>Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data.</li>
<li>Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently.</li>
<li>Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets.</li>
<li>Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions.</li>
<li>Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts.</li>
<li>Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments.</li>
<li>Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams.</li>
<li>Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization.</li>
<li>Comfortable with light travel (approximately 10%) for customer interaction and team needs.</li>
</ul>
This role will require an active TS security clearance. 
Ideally You’d Have: 
<ul>
<li>8+ years of experience building and deploying applied ML systems in production environments.</li>
<li>Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps.</li>
<li>Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation.</li>
<li>Hands-on experience with retrieval systems, embeddings, or representation learning.</li>
<li>Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end.</li>
<li>Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production.</li>
<li>Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity.</li>
</ul>
Nice to Haves: 
<ul>
<li>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.</li>
<li>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.</li>
<li>Hands-on experience with geospatial data or GEOINT: reasoning over maps, imagery, or spatial reference systems.</li>
<li>Depth in model adaptation - training or fine-tuning embedding models, instruction tuning, LoRA/PEFT, or RLHF.</li>
<li>Experience building evaluation infrastructure for non-deterministic systems: LLM-as-judge, regression suites for agent behavior, or drift detection in production.</li>
<li>A track record of turning a forward-deployed prototype into a supported, documented capability other engineers can deploy without you.</li>
</ul><div><div><div>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.</div><div>The base salary range for this full-time position in the location of Washington DC is:</div><div>$274,400—$343,000 USD</div></div></div><div>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 &amp; 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 <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf" rel="noopener noreferrer ugc" target="_blank">Know Your Rights poster</a> 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 <a href="https://scale.com/legal/privacy" target="_blank" rel="noopener noreferrer ugc">privacy policy</a> for additional information.</div>

Staff Machine Learning Engineer, Public Sector

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 <a href="https://scale.com/blog/meet-the-legend-behind-the-name-scale-donovan" rel="noopener noreferrer ugc" target="_blank">Donovan</a> and <a href="https://scale.com/blog/thunderforge-ai-for-american-defense" rel="noopener noreferrer ugc" target="_blank">Thunderforge</a>. 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.
<h3>You will:</h3>
<ul>
<li>Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work</li>
<li>Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them</li>
<li>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</li>
<li>Improve and maintain production models and agents through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics</li>
<li>Build agent-level evaluation benchmarks, LLM judges, and verifiers - and use it to hillclimb performance rather than just report on it</li>
<li>Partner with product and research teams to scope and shape high-impact initiatives, including for upcoming product lines</li>
<li>Build scalable machine learning infrastructure to automate and optimize our ML services</li>
<li>Work directly with government users and subject-matter experts, and translate what you learn into technical direction</li>
<li>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</li>
<li>Communicate technical tradeoffs clearly to non-technical stakeholders</li>
<li>Treat security and compliance as design constraints to engineer around rather than blockers to route past</li>
<li>Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations</li>
<li>Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment</li>
<li>Comfortable with light travel (approximately 10%) for customer interaction and team needs</li>
</ul>
This role will require an active TS security clearance
<h3>Ideally You'd Have:</h3>
<ul>
<li>5+ years of experience building and deploying applied ML systems in production environments</li>
<li>Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment</li>
<li>A track record of owning architectural decisions and defending the tradeoffs behind them - not just implementing a design handed to you</li>
<li>Experience shipping agentic systems with real production traffic and evaluation rigor, rather than prototypes or demos</li>
<li>Solid background in algorithms, data structures, and object-oriented programming</li>
<li>Strong programming skills in Python, experience in PyTorch or Tensorflow</li>
<li>Experience mentoring or reviewing the work of other engineers</li>
</ul>
<h3>Nice to Haves:</h3>
<ul>
<li>Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization</li>
<li>Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments</li>
<li>Experience with computer vision, generative AI models, large language models, or agentic systems</li>
<li>Familiarity with ML evaluation frameworks and agentic model design</li>
<li>Experience deploying ML in classified, air-gapped, or IL5+ environments</li>
<li>Geospatial or GEOINT experience</li>
<li>Inference optimization experience </li>
<li>Fine-tuning experience: SFT, RL, or embedding models</li>
</ul><div><div><div>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.</div><div>The base salary range for this full-time position in the location of Washington DC is:</div><div>$196,000—$294,000 USD</div></div></div><div>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 &amp; 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 <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf" rel="noopener noreferrer ugc" target="_blank">Know Your Rights poster</a> 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 <a href="https://scale.com/legal/privacy" target="_blank" rel="noopener noreferrer ugc">privacy policy</a> for additional information.</div>

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