Lead Machine Learning Engineer (Safety)

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

Why Faculty?

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

About the role

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:

• You have significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes.

• You bring exceptional software engineering fundamentals and advanced Python expertise, with a focus on building resilient, enterprise-ready systems.

• You demonstrate deep hands-on experience with cloud platforms (AWS, Azure, GCP), scalable cloud architectures, container orchestration (Docker, Kubernetes), agent sandboxing, and end-to-end cybersecurity.

• You possess mastery over the full ML lifecycle, with proven expertise operationalising production systems using PyTorch, TensorFlow, or similar frameworks.

• You excel in fast-paced, high-growth environments, bringing autonomy, strategic ownership, and a track record of guiding technical decisions.

• You communicate persuasively with both technical teams and senior non-technical stakeholders, translating complex technical risks into clear strategic direction.

The Interview Process

1. Talent Team Screen (30 minutes)

2. Introduction to the Hiring Manager (30 minutes)

3. Pair Programming Interview (90 minutes)

4. System Design Interview (90 minutes)

5. Commercial & Leadership Interview (60 minutes)

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals foster diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.