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Lead Machine Learning Engineer (Safety)
Faculty · London, England · Posted 16 days ago
"Set the engineering benchmark for safe, secure ML deployment while advising senior client leadership and partnering with Frontier Labs on safety evaluations."
As a Lead Machine Learning Engineer at Faculty, you’ll drive the technical strategy, architecture, and deployment of cutting-edge, secure AI systems across high-stakes domains. Bridging AI research and production impact, you’ll set the benchmark for engineering excellence and operationalise scalable ML infrastructure.
Working alongside Frontier Labs, you will champion practical, safety-first AI frameworks, model capability evaluations, and multi-agent systems. You will act as a principal advisor to client leadership, mentor engineering talent, and steer cross-functional teams to solve critical, real-world AI challenges.
WHAT YOU'LL BE DOING:
- Steering technical strategy, system architecture, and rigorous capability testing for complex ML systems and Frontier AI models
- Architecting production-grade, secure ML software, orchestration tools, and scalable cloud infrastructure
- Establishing company-wide standards and best practices for safe, reliable, and ethical machine learning deployment at scale
- Collaborating with cross-functional teams and executive stakeholders to translate high-impact client needs into resilient AI solutions
- Advising senior clients and partners as a trusted AI safety and technical authority, articulating complex strategies clearly
- Mentoring and developing engineering talent, actively elevating team capabilities and nurturing an inclusive, high-performing culture
- Partnering with Frontier Labs to advance safety evaluation procedures, multi-agent harness tooling, and robust AI governance frameworks
WHO WE'RE LOOKING FOR:
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This role is one of 567 Machine Learning Engineer openings and centers on Llm, Multi-agent Systems, AI Safety Evaluation, and Python. There are 88 open roles at Faculty right now.
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