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Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Senior Applied AI Engineer, you'll own the AI behaviour of production systems our clients depend on, including the agents, evaluations, and backend integration behind them. You'll lead delivery for your workstream and act as the technical point of contact for clients on how their AI performs on live data.
What you'll do- Own the AI layer of production systems for public sector clients, including agents, model integration, and the backend services they run on
- Build production agents from established architectural patterns, with reliable tool calling, guardrails, and observability
- Select and adapt established evaluation methods, and design new evaluations for client-specific risks where the use case requires them
- Apply context engineering, retrieval-augmented generation, model adaptation, or inference optimisation where the use case calls for them
- Investigate regressions in the systems you own, lead root-cause analysis, and implement preventative changes
- Lead project planning for your workstream and manage client expectations on scope, risk, and delivery
- Codify recurring client work into reusable tooling, evaluation components, or guidance that other engineers adopt
- Mentor engineers through code review, pairing, and delegated ownership
- Backend engineering experience, with a track record of taking AI/ML systems into production and keeping them reliable
- Experience owning the AI behaviour of a production system end to end, rather than delivering a component scoped by another team
- Experience designing evaluations that tie model behaviour to real-world outcomes, and using them to catch regressions
- Experience leading root-cause analysis on a production AI or ML system
- Comfort working directly with clients, including explaining model behaviour and trade-offs to non-technical stakeholders
- Experience handling regulated or sensitive data and designing for auditability; sovereign or on-premise deployment experience is valuable
Your primary accountability covers production AI behaviour, its backend integration, and the evaluation required for a specific customer. Senior Full-Stack Engineers own the complete user-facing application and its infrastructure. ML Research Engineers lead novel agent architecture and the benchmark methodology used across accounts. The roles work together on agents and evaluation, with accountability set by the scope of the problem.
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 [email protected]. 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.
Skills Required
- Backend engineering experience with a track record of deploying and maintaining reliable AI or machine learning systems in production
- Experience owning the AI behavior of a production system end to end
- Experience designing evaluations that connect model behavior to real-world outcomes and identify regressions
- Experience leading root-cause analysis on production AI or machine learning systems
- Ability to work directly with clients and explain model behavior and trade-offs to non-technical stakeholders
- Experience handling regulated or sensitive data and designing systems for auditability
- Sovereign or on-premise deployment experience
Scale AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Scale AI and has not been reviewed or approved by Scale AI.
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Healthcare Strength — Company materials and third‑party pages describe comprehensive medical, dental, and vision coverage along with mental‑health services and an EAP. Health insurance is portrayed as strong, with options like HSA/FSA and indications of high premium coverage.
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Leave & Time Off Breadth — Descriptions highlight generous PTO, paid holidays and sick time, bereavement, volunteer time, and role‑dependent flexibility or remote options. This breadth is positioned as part of a supportive time‑off approach, with specifics varying by location.
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Equity Value & Accessibility — Full‑time offers commonly include equity and an ESPP, which can meaningfully lift total compensation, especially in engineering and senior roles. Job postings and compensation snapshots consistently reference base‑plus‑equity packages aligned with competitive AI market pay.
Scale AI Insights
What We Do
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
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