UK remote
Release Manager - AI Models
About this role
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Our engineering teams bring together ML engineering, evaluation and data science, software platform, testing, and product to turn breakthrough autonomous-driving technology into reliable products.
Model releases connect these disciplines, taking AI models from early hypotheses through training, evaluation, and on-road testing to deployment across our vehicle fleet. As our Release Manager — AI Models, you’ll help ensure that a core part of our technology — the AI model — is released reliably, on time, and to the standard required for production. You’ll bring structure and disciplined release practices to the fast-paced, non-deterministic world of ML, building the processes and systems that support clarity, stability, and business goals.
🧠 Your day-to-day Own the model release cycle, maintaining a steady and predictable cadence while adapting to changing business priorities. Coordinate across ML engineering, evaluation and data science, software platform, testing, and product to keep releases moving and resolve dependencies. Run the gates that promote models from hypothesis → training → evaluation → validation → deployment, making clear what is ready to ship and what needs more work.
Drive investigations into regressions and integration issues, coordinate rollback or roll-forward decisions, and follow through on technical debt and corrective actions. Be the central point of contact for model-release status, risks, and timelines, giving engineers and leadership the right level of detail. Run post-release reviews and turn lessons learned into practical improvements across teams. 🧩 What you’ll be working on: Release gates and promotion criteria: Define and justify what it takes for a model to progress, balancing performance gains, reproducibility, product requirements, safety, and compatibility with the onboard software stack and vehicle platform.