Wayve
Release Manager — AI Models

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The role
At Wayve, you'll help deliver the value of our breakthrough autonomous-driving technology by ensuring that a core part of our it — the AI model — is released reliably, on time, and to the standard required for production.
As our Model Release Manager, you'll own how new AI models move through the full lifecycle — from hypothesis, through training, evaluation, and on-road testing, to deployment across our vehicle fleet — balancing the fast-paced, non-deterministic nature of ML with structure and disciplined release practices.
We're looking for someone pragmatic, methodical, and system-minded — someone who understands how model releases fit into the broader engineering, evaluation, and product ecosystem, and who introduces the processes and systems needed to achieve stability, clarity, and business goals. This role rewards two things together: strong release-engineering instincts, and the judgment to know where a non-deterministic, hypothesis-driven system breaks those instincts and where it doesn't. If you have the first and are hungry to build the second fast, this is worth a conversation.
Key responsibilities:
- Model release planning & coordination: Own the model release cycle, maintaining a steady and predictable cadence for shipping new models while adapting to business priorities.
- Gating & promotion: Define and run the gates that promote a model from hypothesis → training → evaluation → validation → deployment. Define and justify the promotion criteria that determine what ships and what is deferred — balancing performance gains, reproducibility, product requirements, safety, and integration compatibility with the onboard software stack and vehicle platform.
- Issues management: Drive investigations and follow-up actions on regressions, integration issues, and technical debt; manage rollback/roll-forward of model versions.
- Bottleneck identification & improvement: Identify constraints in the model-release process and drive improvements. Implement dashboards and KPIs for visibility, and proactively escalate gaps.
- Process & systems building: Understand how model releases fit into the wider system of model development, evaluation, Wayve onboard stack, and product; build processes and frameworks that support clarity, stability, and business goals.
- Tooling & automation influence: Partner with ML platform and integration teams to shape end-to-end automated release tooling; define requirements that improve developer experience, release efficiency, and stakeholder communication.
- Cross-functional collaboration: Work closely with ML engineering, evaluation and data science, software platform, testing, and product teams to ensure successful and stable model releases.
- Clarity & communication: Act as the central point of contact for model-release status, risks, and timelines, keeping stakeholders informed at the right level of detail.
- Continuous improvement: Run post-release reviews and drive corrective actions across teams.
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About you
In order to set you up for success as a Model Release Manager at Wayve, we're looking for the following skills and experience.
Essential
- 5+ years in release management, software engineering, or a related field.
- Strong understanding of the Software Development Life Cycle (SDLC) and release management practices, including testing strategy, system integration, branching, and versioning.
- Conceptual understanding of ML fundamentals — what training data is, the difference between training and inference, what a model version/checkpoint represents, and why model validation is probabilistic rather than pass/fail.
- Experience with CI/CD pipelines and automation tools (e.g. GitHub, Buildkite, CLI tools).
- Skilled at managing releases in complex, fast-moving systems.
- Comfortable operating with high ambiguity — requirements, architecture, and timelines can shift quickly, and you're able to adapt release processes and tooling as needed.
- Strong problem-solving and decision-making ability, especially in release trade-offs involving limited or ambiguous data.
- Good communication skills, comfortable working with engineers and presenting to leadership.


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Desirable
- Experience in AI/ML, autonomous vehicles, or robotics.
- Familiarity with MLOps methodologies and tooling.
- Experience with ML evaluation practices and tooling — especially for physical systems: simulation, model leaderboards, statistically powered experiments (e.g. A/B or shadow-mode testing).
- Awareness of model hardware and software dependencies.
- BSc or equivalent in Computer Science, Engineering, or a related technical discipline.
This is a full-time role based in our office in London. At Wayve we want the best of all worlds, so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, with time spent working from home.
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