wayve - Release Manager - AI Models

• 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. • It’s a bonus if you also bring: • 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 — including simulation, model leaderboards, and statistically powered experiments such as A/B or shadow-mode testing. • Awareness of model hardware and software dependencies. • A BSc or equivalent in Computer Science, Engineering, or a related technical discipline. • 🌱 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.