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Senior Machine Learning Engineer (Safety)

Faculty
LondonPosted today
Location
London

Why Faculty?

Faculty was established in 2014 because we believed AI would be the most important technology of our time. We've worked with over 350 global customers to transform their performance through human-centric AI. We don't chase hype cycles. We innovate, build and deploy responsible AI which moves the needle. 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.

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. We work at the frontier of high-stakes, high-impact missions, 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 understand that powerful AI systems bring both transformative opportunities and complex risks. 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, you'll 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 have extensive experience working with container and orchestration tools such as 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

Interview Process

  • Talent Team Screen (30 minutes)
  • Pair Programming Interview (90 minutes)
  • System Design Interview (90 minutes)
  • Commercial Interview (60 minutes)

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. 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 use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of – just let us know). Every application is reviewed by a human, never decided by AI.

About Faculty

Faculty helps organizations access cutting-edge AI and use it to improve business performance. The company provides a combination of strategy, software, and skills to create value from artificial intelligence, enabling data scientists to speed up deployment and increase transparency over machine learning models.

Industry
Artificial Intelligence
Head office
London, United Kingdom
Company size
201-500
Founded
2014
Data ScienceArtificial IntelligenceMachine LearningAI StrategyAI GovernanceAI SafetyAI Training & UpskillingAI Solution Development
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Senior Machine Learning Engineer (Safety)