Machine Learning Engineering Manager, ADAS

🧠 Your day-to-day

• Splitting your time roughly 60% management and 40% hands-on, leading a team of around seven ML engineers, made up of new hires and an existing sub-team

• Acting as tech lead across multiple workstreams, setting the vision for how problems get solved, in what order, and with which dependencies

• Reviewing and approving delivery plans for the tasks you own

• Partnering with TPMs on planning and execution, and with Product to help shape priorities

• Coaching and developing the ML engineers on your team, supporting their growth as the team scales

🧩 What you’ll be working on

• Taking our end-to-end AI driving approach into ADAS for a specific OEM production programme

• Bringing ML models from proof of concept through to production on embedded automotive hardware

• Optimising runtime and inference so the right model runs well on constrained hardware, rather than defaulting to the biggest one

• Building and scaling a new team during a high-priority growth phase, with plenty of room to shape how it works

• Working across system boundaries with software, embedded and product teams to deliver a coherent product

👤 You should apply if

• Expert background in developing ML, specifically computer vision

• You are/have been a people manager and enjoy developing engineers

• You’ve worked across systems with software developers and product teams, particularly on embedded software

• You have hands-on experience with embedded runtime and inference optimisation, and make pragmatic trade-offs on model size and performance

• You communicate clearly and thoughtfully with colleagues across sites and cultures

• You stay steady and keep your team moving when requirements are unclear or change often

🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.