Key Notes
Successful delivery of autonomy products built on complex AI models is essential for this director-level position. The remit leads Product Engineering teams across Driving, ADAS, Parking and HMI, converting AI backbones into a production-quality capability roadmap for multiple automotive partners. London is an advertised location for this full-time, hybrid appointment reporting to the VP of Autonomy.
What You'll Work On
- Define the technical vision, strategy and metrics for AV Product Engineering across Driving, ADAS, Parking and HMI teams.
- Convert AI model backbones into a production-quality autonomous-vehicle capability roadmap deployed through separate OEM application teams.
- Set data curricula and evaluation practices that support feature coverage, geographical coverage, predictable KPIs and efficient resource use.
- Lead engineering managers, build technical capability and coordinate career development across multiple teams and management layers.
Why This Role Matters
- Wayve’s autonomous-vehicle capability roadmap turns trained AI backbones into production features for multiple OEM partners, linking model development with deployable Driving, ADAS, Parking and HMI functionality.
- Product Engineering teams share data curricula, evaluation metrics and technical direction; alignment across those controls affects feature coverage, geographical readiness and predictability against programme KPIs.
What They Are Looking For
- Experience: Delivery of successful autonomy products relying on complex AI models is essential.
- Experience: Leadership across complex teams, including multiple management layers or matrix structures, is essential.
- Domain: Autonomy-product experience in autopilot, navigation, active safety or parking is essential.
- Technical: Roadmap articulation, resource allocation, programme planning, code practices, testing and serviceability are essential.
- Qualification: A bachelor’s or master’s degree in Computer Science or Engineering, or similar experience, is essential.
- Preferred: Foundation models, multiple automotive OEMs, generative-AI simulation, cloud platforms, databases or large data pipelines are desirable.