Release Manager - AI Models

Overview

As Release Manager for AI models at Wayve, you own the model release cycle to ensure reliable, on-time production deployment. You’ll bring disciplined release practices to ML-driven workflows spanning development, evaluation, and on-road testing. You’ll coordinate cross-functional teams to move models through gates, resolve dependencies, and drive improvements from post-release learnings. This role sits at the heart of Wayve’s AI platform, enabling scalable, safe autonomous driving solutions.

Pay / Benefits

• salary benchmarked against market
• meaningful equity
• relocation support and visa where applicable
• hybrid working with core hours
• learning and development budgets
• comprehensive health and wellbeing benefits

Responsibilities

• Own the model release cycle with a steady cadence
• Coordinate across ML engineering, evaluation, data science, software platform, testing, and product
• Run release gates from hypothesis to deployment and decide what is ready to ship
• Investigate regressions and integration issues; oversee rollbacks/roll-forwards and technical debt actions
• Be the central contact for release status, risks, and timelines for engineers and leadership
• Conduct post-release reviews and translate findings into improvements
• Define and justify model progression criteria balancing performance, reproducibility, safety, and compatibility
• Build release workflows connecting model development, evaluation, onboard stack, and product needs
• Identify bottlenecks, create dashboards/KPIs, and escalate gaps
• Develop end-to-end automated release tooling with ML platform partners
• Strengthen management of model versions, integrations, and recovery to ensure value delivery

Key requirements

• 5+ years in release management, software engineering, or related field
• Knowledge of SDLC and release management practices, testing strategy, system integration, branching, versioning
• Understanding of ML fundamentals (training vs inference, models/ checkpoints) and probabilistic validation
• Experience with CI/CD pipelines and automation tools (GitHub, Buildkite, CLI tools)
• Proven ability to manage releases in complex, fast-moving systems and adapt processes/tools as needed
• Strong problem-solving and decision-making skills in data-ambiguous scenarios
• Clear communication with engineers and leadership about priorities, risks, and decisions
• Pragmatic, methodical, system-minded with release-engineering instincts
• Bonus: AI/ML, autonomous vehicles, or robotics experience; MLOps tooling; ML evaluation practices for physical systems; model hardware/software dependencies
• strong communication
• problem-solving
• decision-making under ambiguity
• CI/CD pipelines
• GitHub
• Buildkite

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