Lead Machine Learning Engineer (Safety)

The role

You will drive technical strategy, architecture, and deployment of secure AI systems. You will work with Frontier Labs to champion safety-first AI frameworks and mentor engineering talent.

What you will do

• 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
• Mentoring and developing engineering talent
• Partnering with Frontier Labs to advance safety evaluation procedures, multi-agent harness tooling, and robust AI governance frameworks

Required qualifications

• Significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes
• Exceptional software engineering fundamentals
• Advanced Python expertise
• Deep hands-on experience with cloud platforms (AWS, Azure, GCP)
• Scalable cloud architectures
• Container orchestration (Docker, Kubernetes)
• Agent sandboxing
• End-to-end cybersecurity
• Mastery over the full ML lifecycle
• Proven expertise operationalising production systems using PyTorch, TensorFlow, or similar frameworks
• Ability to excel in fast-paced, high-growth environments
• Ability to communicate persuasively with both technical teams and senior non-technical stakeholders

About the company

Faculty was established in 2014 to transform performance through human-centric AI. They work with over 350 global customers across government, finance, retail, energy, life sciences and defence.