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Scale's Global Public Sector team uses AI to address critical challenges facing the public sector around the world. As an Applied AI Engineer, you'll build AI that runs inside production systems used by national health and government organisations.
You'll own scoped components of those systems, such as a model integration, agent tool, API, data pipeline, or evaluation, from implementation through to delivery. Senior engineers set the system-level design and client commitments, so you can go deep on making your components work reliably on real data.
What you'll do- Own the implementation, testing, and delivery of defined AI components within an established system design
- Build agent tools, model integrations, and the backend services and APIs they depend on
- Run and extend evaluations within an established framework, interpret results, investigate common failure modes, and flag regressions
- Debug production issues in the components you own and resolve them using the team's engineering practices
- Communicate progress and blockers early, and take responsibility for delivery dates within your scope
- Work directly with client teams on the requirements and feedback for your components
- Share what you learn with the team as you build public sector domain expertise
- Experience building and shipping production software, with proficiency in Python and working knowledge of at least one of TypeScript, Java, or C++
- Hands-on experience integrating models or AI/ML components into a production application, such as calling LLMs, building retrieval or agent tooling, or deploying a trained model
- A working understanding of ML evaluation: how to read results, spot regressions, and identify common causes of model failure
- Experience owning a defined piece of work through testing, release, and production debugging
- Strong problem-solving skills and a data-driven approach to iterating on models and datasets
- Clear written and verbal communication, including raising blockers and trade-offs early
- A backend or full-stack engineering background, so you can work across the API, service, and data-schema layers of the systems you contribute to
- Experience with cloud ML platforms such as AWS, GCP, or Azure
- Exposure to agentic workflows, retrieval-augmented generation, or context engineering
- Experience handling regulated or sensitive data
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
- Experience building and shipping production software
- Proficiency in Python
- Working knowledge of at least one of TypeScript, Java, or C++
- Hands-on experience integrating AI/ML models or components into a production application
- Working understanding of machine learning evaluation, regressions, and model failure modes
- Experience owning defined work through testing, release, and production debugging
- Strong problem-solving skills and a data-driven approach
- Clear written and verbal communication
- Backend or full-stack engineering background
- Experience with AWS, GCP, or Azure cloud ML platforms
- Exposure to agentic workflows, retrieval-augmented generation, or context engineering
- Experience handling regulated or sensitive data
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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