Senior Forward Deployed Engineer in London

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. 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 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. Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Developed Vetting (DV) and willing to work on site with our clients from time to time.

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. This is an ambitious, cross-functional role requiring a blend of technical expertise, engineering leadership, and confident client-facing skills.

What You'll Be Doing

• Leading technical scoping and architectural decisions for high-impact ML systems
• 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 understand the full ML lifecycle and have significant experience 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), including architecture, security, and infrastructure
• 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)

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.