Senior Machine Learning Engineer (Safety)

Faculty
London, United Kingdom
On-site

Who this role is best for

Aimed at senior machine learning engineers with expertise in AI safety and national security who lead technical strategy and collaborate across disciplines.

Best fit for

  • Candidates with experience in national security and AI safety domains
    — “advancing the responsible development and deployment of AI in support of national security and global stability”
  • Individuals who have led the transition of AI research to real-world systems
    — “lead the bridge between AI research and real-world impact by architecting scalable, production-grade machine learning systems”
  • Engineers with a strong background in deploying LLMs and AI safety evaluation
    — “significant experience building and deploying secure and scalable LLM applications, and are comfortable with multi-agent harness tooling and AI Safety evaluation procedures”

Things to consider

  • The role demands high-stakes, mission-critical work with government and tech organizations
    — “partner with Government and the biggest tech organisations in the world”
  • Candidates must be prepared to work in a fast-paced, high-growth environment
    — “you thrive in fast-paced, high-growth environments”

How to stand out

  • Highlight your experience in deploying AI systems with ethical and operational rigor
    — “designing and building production-grade ML software and infrastructure that meets rigorous operational and ethical standards”
  • Demonstrate leadership in mentoring and shaping engineering culture
    — “mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth”
  • Showcase your ability to translate complex AI concepts into client strategies
    — “acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • deployed scalable ml systems
  • led technical scoping
  • mentored junior engineers
Typical background
phd in computer science or related fieldexperience in ai safety

Skills & requirements

Required

Machine LearningDeep LearningTensorFlowPyTorchAi SafetyMl InfrastructureProduction DeploymentTechnical Leadership

Preferred

Natural Language ProcessingComputer VisionCloud ComputingEthical Ai

Stack & domain

TensorFlowPyTorchAI Safety Evaluation ProceduresLLM ApplicationsMulti-agent Harness ToolingLeadershipTechnical StrategyMentorshipCollaborationCommunicationNational SecurityAI SafetyMachine LearningProduction-grade ML Software

About the role

Original posting from Faculty via Ashby

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 https://faculty.ai/impact.

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 TEAM

Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions.

We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all.

ABOUT THE ROLE

As a Senior Machine Learning Engineer, we’ll look to you to lead development and deployment of cutting-edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards.

You will lead the bridge between AI research and real-world impact by architecting scalable, production-grade machine learning systems. Partnering directly with clients and cross-functional teams, you will drive technical strategy, mentor teams on best practices, and collaborate with Frontier Labs to define and reinforce our industry leadership in practical, high-stakes AI safety.

WHAT YOU'LL BE DOING:

  • Leading technical scoping and architectural decisions for high-impact ML systems and capability testing of Frontier AI models
  • Designing and building production-grade ML software, tools, and scalable infrastructure
  • Defining and implementing best practices and standards for deploying machine learning at scale across the business
  • Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities
  • Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
  • Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth

WHO WE'RE LOOKING FOR:

  • You have significant experience building and deploying secure and scalable LLM applications, and are comfortable with multi-agent harness tooling and AI Safety evaluation procedures.
  • You understand the full ML lifecycle and are confident operationalising models built with frameworks like TensorFlow or PyTorch
  • You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems
  • You have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) specifically cloud architecture, infrastructure management, and end-to-end cybersecurity practices
  • You've extensive experience working with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale
  • You thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion
  • You communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders

OUR INTERVIEW PROCESS

  • Talent Team Screen (30 minutes)
  • Pair Programming Interview (90 minutes)
  • System Design Interview (90 minutes)
  • Commercial 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.

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.

Source: Faculty careers (Ashby)

Similar roles