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 Team

Bringing medicine to patients is complex, expensive and high-risk. Faculty’s Life Science’s team is concentrated on building AI solutions which optimise the research and commercialisation of life-changing therapies.

We partner with major pharma firms, academic research centres and MedTech start-ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health 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.

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

The 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. 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.