Faculty
Lead Machine Learning Engineer
Is this role open to you?
London
Confirm work authorization, visa sponsorship and location requirements with the employer.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
Join us as a Lead Machine Learning Engineer to spearhead the technical direction and delivery of complex, innovative AI and software projects. You will act as a technical expert, applying your skills across various projects from solution architecture to client-side deployments, while ensuring engineering decisions are sound and reliable.
This role demands a balance of deep technical expertise and strong leadership, focusing on driving innovation, fostering team growth, and building reusable solutions across the organisation. If you're ready to manage high-risk projects and deliver practical, innovative outcomes, this is your chance to shape our future.
What you'll be doing
Setting the technical direction for complex ML and software projects, balancing trade-offs, and guiding team priorities
Architecting, implementing, and maintaining reliable, scalable ML/software systems, and justifying key architectural decisions.
Defining project problems, developing roadmaps, and overseeing delivery across multiple workstreams in often ill-defined, high-risk environments.
Driving the development of shared resources and libraries across the organisation and guiding other engineers in contributing to them.
Leading hiring processes, making informed selection decisions, and mentoring multiple individuals to foster team growth.
Proactively developing and executing recommendations for adopting new technologies, tools and changing our ways of working to stay ahead of the competition.
Acting as a technical expert and coach for customers, accurately estimating large work-streams and defending rationale to stakeholders.
Who we're looking for
You are a technical expert among your peers, capable of going deep on particular topics and demonstrating breadth of knowledge to solve almost any problem.
You possess strong software engineering skills in Python and at least one compiled or strongly-typed language (e.g. Go, Java, Rust, or TypeScript), and know how to build robust, production-grade systems.
You are an expert in at least one major Cloud Solution Provider (e.g., Azure, GCP, AWS) and have led teams to build full-stack web applications.
You have hands-on experience with containerisation tools like Docker and orchestration via Kubernetes.
You can successfully manage and coach a team of engineers, setting team-wide development goals to improve client delivery.
You find novel, clever solutions for project delivery and take ownership for successful project outcomes.
You're an excellent communicator who can proactively help customers achieve their goals and guide both technical teams and non-technical stakeholders.
Our Interview Process
Talent Team Screen (30 minutes)
Introduction to the role (45 minutes)
Pair Programming Interview (90 minutes)
System Design Interview (90 minutes)
Commercial & Leadership 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.
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