Principal Machine Learning Engineer, Driving Product

Overview

Join Wayve to lead and scale the end-to-end driving model powering our L2 autonomous driving product. You’ll guide a compact, high-impact team and own data, model, and release readiness while solving real-world road issues. Partner with OEMs and cross-functional stakeholders to deliver improvements that meet safety and performance KPIs. This role blends hands-on engineering with leadership to shape how our technology evolves across geographies and vehicle platforms. You’ll help write the future of embodied AI in mobility.

Pay / Benefits

• salary benchmarked against market
• meaningful equity
• relocation support and visa sponsorship
• hybrid working with core hours
• learning and development budgets
• comprehensive benefits (health/dental, parental leave, pension)

Responsibilities

• Lead the Driving Product Team, balancing hands-on coding with team leadership
• Diagnose high-impact on-road issues, root-cause analysis, and iterative fixes through data and model changes
• Own data recipes, model architecture, evaluation, and release readiness for the driving model
• Collaborate cross-functionally to resolve model and vehicle interface problems
• Code and run experiments as a senior hands-on developer while guiding priorities
• Scale the end-to-end driving model across geographies and vehicle platforms
• Drive data-led iteration cycles using road and off-road evaluations
• Grow and shape the driving model program and team size as it scales

Key requirements

• Highly technical with hands-on Python coding and model/data iteration experience
• Experience delivering deployed ML models in robotics or autonomous vehicles
• Productionising ML models in industry and delivering incremental live-system improvements
• Focused on production impact rather than pure research
• Able to operate as individual contributor or tech lead, with potential to manage a small team
• Interest in autonomy and willingness to learn if not all criteria are met

• cross-functional collaboration
• strong communication
• ownership and initiative
• Python
• ML model deployment
• data iteration for embodied AI

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