Director Av Product Engineering

Wayve Wayve · Robotics · London, United Kingdom +1 · AV Engineering

Director of Engineering for Product Engineering within the AI Engineering organization, responsible for taking AI model backbones and delivering an autonomous vehicle capability roadmap with production-level quality. This includes data collection, filtering, training, tuning, and debugging production models for deployment to OEM partners. The role requires establishing ML practices, attracting technical leadership, and managing multiple teams covering driving, ADAS, parking, and HMI functionality. Key responsibilities include defining technical vision and strategy, driving an eval-driven culture, and building technical capabilities.

What you'd actually do

  1. Define and own the technical vision, strategy and metrics for your area, ensuring its teams and the rest of Wayve are aligned and galvanised.
  2. Frame autonomous driving as a problem that can be solved by data. Define efficient data curriculums to ensure product feature and geographical coverage.
  3. Drive an eval-driven culture to reach KPI targets with high predictability and resource efficiency.
  4. Partner with the senior leadership team to maintain a culture of impact, performance, and health.
  5. Build technical capabilities across the division and develop talented engineers as Wayve grows. Build resilient and reliable systems, teams and individuals.

Skills

Required

  • Management experience leading complex teams
  • Experience with autonomy products – autopilot/navigation, active safety, parking
  • Roadmap articulation
  • Interface with leadership & business functions
  • Resource allocation
  • Program planning and execution
  • Code development practices
  • Testing
  • Serviceability

Nice to have

  • Experience applying foundation models to implement specific product features
  • Experience working with multiple automotive OEMs
  • Experience with GenAI simulation
  • Experience with cloud platforms, databases, large scale data pipelines

What the JD emphasized

  • delivered successful Autonomy products that rely on complex AI models
  • experience with autonomy products
  • Product delivery skills
  • Execution skills
  • Engineering skills

Other signals

  • delivering autonomous vehicle capability roadmap with production-level quality
  • establish solid ML practices
  • attract technical leadership
  • define and own the technical vision, strategy and metrics for your area
  • drive an eval-driven culture to reach KPI targets with high predictability and resource efficiency