Lead ML Engineer: Strategy, Security & Scalable AI

Faculty; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Faculty is seeking a Lead Machine Learning Engineer in London to drive the technical strategy, architecture and deployment of secure AI systems across high-stakes domains. You will bridge AI research and production, set engineering standards and lead cross-functional teams to deliver scalable ML infrastructure.

You will mentor engineers, advise senior clients, and partner with Frontier Labs on safety evaluation procedures and governance frameworks, shaping responsible AI at scale.

Qualifications

• Significant leadership experience designing, deploying, and securing scalable ML applications and AI safety evaluations.
• Strong software engineering fundamentals and advanced Python expertise for enterprise systems.
• Deep hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization.

Responsibilities

• Steer technical strategy, system architecture, and capability testing for complex ML systems and Frontier AI models.
• Architect production-grade, secure ML software, orchestration tools, and scalable cloud infrastructure.
• Establish company-wide standards for safe, reliable, and ethical ML deployment at scale.
• Collaborate with cross-functional teams and executives to translate client needs into resilient AI solutions.
• Advise senior clients as a trusted AI safety and technical authority, articulating complex strategies clearly.
• Mentor and develop engineering talent, elevating team capabilities and fostering an inclusive, high-performing culture.
• Partner with Frontier Labs to advance safety evaluation procedures, multi-agent tooling, and AI governance frameworks.

Skills

ML leadership

LLM architectures

Python engineering

Cloud platforms

Security & ethics

Cross-functional collaboration

Job description

Faculty is seeking a Lead Machine Learning Engineer in London to drive the technical strategy, architecture and deployment of secure AI systems across high-stakes domains. You will bridge AI research and production, set engineering standards and lead cross-functional teams to deliver scalable ML infrastructure.

You will mentor engineers, advise senior clients, and partner with Frontier Labs on safety evaluation procedures and governance frameworks, shaping responsible AI at scale.