Key Notes
Wayve’s simulation, evaluation and validation platforms sit under one product strategy covering developer tools, synthetic data, critical-event pipelines and release gating. The role requires 8+ years in product management, including at least 3–5 years leading PM teams, plus experience building internal platforms or ML/AI evaluation infrastructure. London is a hiring location under Wayve’s hybrid working policy.
What You'll Work On
- Set multi-year product vision and strategy for simulation, evaluation, synthetic-data, critical-event and validation platforms used to assess the AI Driver.
- Own the end-to-end roadmap across simulation, evaluation and validation, resolving customer trade-offs and communicating resourcing decisions to director-level stakeholders.
- Lead and develop product managers across Simulation, Evaluation, Data and Validation, using hiring and mentoring to close capability gaps.
- Define platform standards for reliability, latency, evaluation cost, self-service, observability and API stability, then run monthly and quarterly reviews.
Why This Role Matters
- Wayve’s AI Driver release decisions use simulation, evaluation and validation outputs, making platform metrics and quality standards part of the evidence for on-road deployment.
- Autonomy and Science teams depend on the platform roadmap to balance developer velocity, signal quality, evaluation cost and time-to-insight across connected tools and datasets.
What They Are Looking For
- Experience: Eight or more years in product management, including at least three–five years leading PM/senior-PM teams, is essential.
- Experience: Building internal platforms, developer tools or ML/AI evaluation infrastructure for engineers and scientists is essential.
- Technical: Systems thinking across hardware, AI and product, and evidence of analysis that changed a complex AI/robotics go/no-go decision, are essential.
- Technical: Customer-facing KPIs, user-experience measurement and regular, leading use of AI tools in the work are essential.
- Preferred: Autonomous vehicles, robotics, safety-critical AI/ML, simulation, synthetic data or production ML observability experience is desirable.
- Preferred: SOTIF/ISO 21448, ISO 26262 or other learned-system safety standards, and scaled developer/ML/data platforms, are desirable.