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Staff Applied AI Engineer

Scale AI· GPS Engineering
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London, UKfull-timePosted 2mo ago

About the role

Senior AI engineering role focused on defining standards, governance, and production MLOps for Scale's Global Public Sector team. Leads high-risk AI systems, sets technical roadmaps, and acts as senior technical partner to client leadership on AI strategy.

Responsibilities

  • Define standards for responsible AI, model governance, and production MLOps that get adopted broadly across the Global Public Sector team
  • Build or validate the highest-risk parts of strategic AI systems and use those systems to establish standards other teams can adopt
  • Architect AI systems designed to prevent systemic failure, and lead the resolution of the most severe incidents tied to model safety or data integrity
  • Build reusable AI capabilities, such as production-ready agent implementations built on proven architectures, fine-tuned models, or evaluation methodologies, that other engineers and clients can build on
  • Advise on which new AI developments are worth adopting, and help set the technical roadmap for the domain
  • Act as the senior technical partner to client leadership on AI strategy
  • Coach Senior Applied AI Engineers, delegate ownership of technical domains, and build systems and practices that enable multiple teams to deliver safer AI
  • Contribute to recruiting and representing Scale's AI work externally

Qualifications

  • 7+ years of engineering experience, with a multi-year track record owning AI/ML systems in production
  • Experience judging the quality of training data, selecting the right adaptation method for a given model, evaluating fine-tuning results, and balancing serving cost, latency, and quality trade-offs
  • Experience owning an AI-powered product end to end, including direct involvement in the AI's behaviour rather than implementing ML work scoped by another team
  • A track record of establishing standards that outlived the projects they were built for, such as an evaluation methodology, an MLOps practice, or an architectural pattern
  • Comfort operating with executive-level clients and leadership, including defending a technical position under pressure
  • Deep experience with regulated, sovereign, or on-premise AI deployment, including hallucination mitigation and auditability

Skills

Required:AI/ML systems ownershipData quality evaluationMLOpsRegulated/on-prem AI deploymentExecutive communicationLeadership/mentoring
Nice to have:Agent architectures

Benefits

  • Not specified in the description
Last updated Aug 5, 2026. Interested? Apply on the company site.
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About Scale AI

Data-centric infrastructure to accelerate the development of AI

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

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