Scale AI
Machine Learning Engineer, Global Public Sector
Remote GPS Engineering role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalOpen level
Work settingRemote
Accepted candidate locations
United Kingdom
Role overview
Machine Learning Engineer, Global Public Sector
Requirements and responsibilities
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Details
- Creating custom AI applications that will impact millions of citizens
- Generating high-quality training data for national LLMs
- Upskilling and advisory services to spread the impact of AI
The Mission
- Applied Agent Research: Leading the design of reliable, multi-step agentic systems and long-horizon reasoning frameworks that can solve complex problems for national security and public policy.
- Systemic Evaluation & Red-Teaming: Developing rigorous benchmarks and evaluation protocols to ensure AI systems are safe, unbiased, and performant in high-stakes, non-commercial environments.
- Model Optimisation & Selection: Conducting deep-dive research into model performance (both open-weight and closed) to identify the best tools for niche domains, optimising them through context engineering, RAG, and other inference-time techniques.
What You Will Do
- Architect Agentic Systems: Design and build agent architectures, the harnesses, tool-use protocols, and logic flows that allow LLMs to function as reliable, autonomous agents in complex workflows.
- Drive Reliability & Safety: Research and implement robust evaluation frameworks. This includes red-teaming for sovereign AI requirements and developing strategies to mitigate hallucinations in regulated data environments.
- Synthesise Deep Research: Build agents capable of autonomous information synthesis and long-horizon reasoning, enabling users to analyse massive datasets and extract actionable insights.
- Optimize for Niche Domains: Evaluate and adapt models for specialised use cases, such as LLM reasoning for low-resource languages, complex OCR tasks, or working in GPU-constrained environments
- Build Evaluation Frontiers: Create new, automated benchmarks that define what success looks like for AI in the public sector, ensuring our systems meet the highest standards of accuracy and sovereignty.
- Consult as a Technical Authority: Act as a subject matter expert for public sector leaders, advising on the practical limits, safety requirements, and performance trade-offs of emerging AI technologies.
Ideally, You Have
- Engineering Rigour: Exceptional proficiency in Python and experience building agentic harnesses or AI infrastructure. You write production-ready code that is modular, scalable, and reliable.
- Applied Research Mindset: A track record of taking theoretical AI concepts and turning them into functional prototypes or products. You know how to read a paper and determine if its methods are actually viable for a production system.
- Evaluation Expertise: Experience in LLM benchmarking, red-teaming, or building evaluations that go beyond standard academic datasets.
- Advanced Degree: A Master’s or PhD in Computer Science, Mathematics, or a related field (with a focus on ML) is preferred, but we value demonstrated impact and engineering excellence.
Nice to Haves
- Agentic Systems Expert: Deep experience in building multi-agent systems, including chain-of-thought optimisation and tool-calling reliability.
- Sovereign AI Experience: Experience working with highly regulated data environments, on-premise deployments, or sensitive government use cases.
- Inference Optimisation: Knowledge of how to optimise model performance for environments with limited GPU capacity or specific latency requirements.
- Zero-to-One Mindset: You are comfortable navigating ambiguity and enjoy defining research directions from scratch to solve a specific product or mission need.
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