SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Wayve is building an end-to-end AI platform for autonomous driving that enables vehicles to learn directly from real-world experience. The company is pioneering a mapless, hardware-agnostic approach that integrates with global OEM partners to unlock advanced levels of automation from L2+ through L4.
In this role, you will lead the AI Validation team's efforts to build trust in the Wayve AI Driver. You'll own validation strategy for advanced driver-assistance and autonomous-driving functions across multiple test modalities—both simulated scenarios and physical vehicle testing. Your day-to-day responsibilities include:
- Leading validation strategy for ADAS and autonomy functions, translating product and safety requirements into measurable coverage, acceptance criteria, and validation plans
- Working hands-on with Python-based evaluation tools, metrics, simulation results, and large datasets to implement behaviour metrics and evidence
- Analysing validation outcomes and communicating clear evidence to Product, Safety, Release, and Autonomy Engineering stakeholders
- Coordinating dependencies across data, simulation, evaluation, and engineering teams to ensure validation runs reliably at scale
- Providing technical leadership and raising the quality bar for systems validation in fast-moving, ambiguous programmes
- Building comprehensive verification strategies, test suites, and scalable, automated validation workflows that support multiple products and customer deployments
- Developing validation approaches for learned and adaptive behaviours as end-to-end AI systems evolve
You'll be working in a hybrid model across Wayve's main hubs (London, Sunnyvale, Yokohama, Herzliya, Vancouver, Leonberg), with the Sunnyvale office as your primary location. The role offers hands-on involvement in vehicle workshops and labs alongside strategic leadership.
REQUIREMENTS:
- Significant experience validating complex automotive, autonomous-driving, robotics, aerospace, or similarly safety-relevant systems
- Demonstrated track record leading validation concepts from initial ambiguity through implementation, execution, and reporting
- Proficiency in Python to implement metrics and work within evaluation codebases; SQL experience is valuable
- Understanding of both simulated and physical testing with ability to make evidence-based decisions from imperfect data
- Strong communication skills, excellent documentation practices, and ability to align technical stakeholders across disciplines
- Beneficial: experience with ML, computer vision, motion planning, data science, SOTIF, safety validation, or agentic AI workflows
- Note: The posting explicitly welcomes applications from candidates who don't meet every requirement but are passionate about autonomy and keen to learn
