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Scale's Global Public Sector team is seeking a Staff Applied AI Engineer to lead the development and governance of AI systems for critical public sector challenges worldwide. In this role, you will define and establish standards for responsible AI, model governance, and production MLOps practices that are adopted across the team. You'll architect high-risk AI systems designed to prevent systemic failure, lead incident resolution for model safety and data integrity issues, and build reusable AI capabilities such as production-ready agent implementations and evaluation methodologies that other engineers and clients can leverage.
Key responsibilities include building or validating the highest-risk components of strategic AI systems, establishing standards that outlive individual projects, advising on emerging AI developments and technical roadmap direction, and serving as the senior technical partner to client leadership on AI strategy. You will coach Senior Applied AI Engineers, delegate technical domain ownership, and build systems and practices that enable multiple teams to deliver safer AI. Additionally, you'll contribute to recruiting and representing Scale's AI work externally.
You bring 7+ years of engineering experience with a multi-year track record owning AI/ML systems in production. You have deep expertise in judging training data quality, selecting appropriate model adaptation methods, evaluating fine-tuning results, and balancing serving cost, latency, and quality trade-offs. You've owned AI-powered products end-to-end with direct involvement in AI behavior, and have a proven track record of establishing standards such as evaluation methodologies, MLOps practices, or architectural patterns. You're comfortable operating with executive-level clients and leadership, and have deep experience with regulated, sovereign, or on-premise AI deployment, including hallucination mitigation and auditability.
The role sits within Scale's Global Public Sector team, where you'll work alongside Senior Full-Stack Engineers who own user-facing applications and infrastructure, and ML Research Engineers who lead novel agent architecture. Location, travel, and vetting requirements vary by assignment; some UK assignments may require BPSS screening and potentially SC or DV clearance depending on the account.
