Release Manager - AI Models

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. 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.

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.
• A release process that works for ML: Build frameworks that connect model development, evaluation, the Wayve onboard stack, and product needs , applying strong release-engineering practices while recognising where hypothesis-driven, non-deterministic systems need a different approach.
• Bottleneck identification and improvement: Find constraints in the release lifecycle, implement dashboards and KPIs to make them visible, and proactively escalate gaps.
• Tooling and automation: 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.
• Reliable, stable deployments: Strengthen how teams handle model versions, integration issues, regressions, and recovery so that releases deliver value reliably.

You Should Apply If

• You have 5+ years of experience in release management, software engineering, or a related field.
• You understand the Software Development Life Cycle (SDLC) and release management practices, including testing strategy, system integration, branching, and versioning.
• You have a conceptual understanding of ML fundamentals: what training data is, the difference between training and inference, what a model version or checkpoint represents, and why model validation is probabilistic rather than simply pass/fail.
• You have experience with CI/CD pipelines and automation tools such as GitHub, Buildkite, and CLI tools.
• You're skilled at managing releases in complex, fast-moving systems and comfortable adapting processes and tooling as requirements, architecture, and timelines change.
• You bring strong problem-solving and decision-making skills, including when release trade-offs depend on limited or ambiguous data.
• You communicate clearly with engineers and leadership, helping people understand priorities, risks, and decisions.
• You're pragmatic, methodical, and system-minded. You bring strong release-engineering instincts and are keen to develop the judgment to know where ML systems require a different approach.