Lead Machine Learning Engineer (Safety)

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

Job summary

Faculty is seeking a Lead Machine Learning Engineer to shape technical strategy, architecture, and deployment of secure AI systems across high-stakes domains. You will bridge AI research and production, setting the standard for scalable ML infrastructure and governance.

You’ll lead cross‑functional teams, mentor engineers, and collaborate with Frontier Labs to advance safety evaluation procedures, multi‑agent tooling, and ethical deployment at scale for real‑world client challenges.

Qualifications

• Significant leadership experience designing, deploying, and securing scalable ML systems.
• Exceptional software engineering fundamentals with advanced Python expertise.
• Deep hands-on cloud experience across AWS/Azure/GCP and container orchestration.

Responsibilities

• Steer technical strategy, system architecture, and 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.

Skills

Leadership experience

Python

Enterprise software design

ML lifecycle mastery

Stakeholder communication

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

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

• Talent Team Screen (30 minutes)

• Introduction to the Hiring Manager (30 minutes)

• Pair Programming Interview (90 minutes)

• System Design Interview (90 minutes)

• Commercial & Leadership Interview (60 minutes)

#LI-PRIO

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters 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.

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.