Tech Lead Manager - ML Autonomy Performance

As Tech Lead Manager in Wayve’s Driving Product Team, you will guide a small team and shape the Robotaxi driving model that powers our autonomous vehicles. You’ll balance hands-on engineering with people leadership, driving data- and model-driven improvements to performance across cities and vehicle platforms. You will own data recipes, model architecture choices, and release readiness, collaborating with cross-functional partners to resolve interface and deployment challenges. This role places you at the core of production ML for autonomous driving, directly supporting global Robotaxi launches. You’ll help scale a high-impact team within a mission-driven company building mapless, hardware-‑

• salary benchmarked against market annually
• meaningful equity
• relocation support and visa sponsorship where applicable
• hybrid working with core hours
• learning and development budgets
• comprehensive benefits (health, dental, pension, wellbeing programs)

• Lead a small team (up to five) focused on Robotaxi driving performance, blending technical work with leadership
• Diagnose high-impact on-road issues, uncover root causes, and implement fixes via data and model iteration
• Own changes to data recipes, model architecture, evaluation, and release readiness for the driving model
• Collaborate with cross-functional teams to resolve model and vehicle interface problems
• Act as a hands-on developer, writing code, running experiments, and setting team priorities
• Contribute to end-to-end driving model development powering Wayve's Robotaxi product
• Scale driving performance across cities and platforms while meeting KPIs
• Lead data-driven iteration to close performance gaps through on-road and off-road evaluation
• Grow and shape a small, high-impact team as the Robotaxi program scales

• Has managed engineers before and seeks to lead while remaining deeply technical (Tech Lead Manager)
• Strong Python skills and hands-on ML/model/data iteration capability
• Experience delivering deployed production ML models or productionizing ML in live systems
• Experienced with production-focused ML work rather than purely research or early-stage exploration

• technical leadership
• cross-functional collaboration
• data-driven decision making
• Python
• model and data iteration
• production ML systems