Senior Machine Learning Engineer, Driving Product

Wayve • Sunnyvale, CA

23h • Hybrid

About The Position

The Senior Machine Learning Engineer will develop and ship AI-driver models and core driving behaviours for Level 2 through Level 4 autonomous driving. The Driving Product team takes models from data and training through evaluation and on-road validation, delivering them on commercial timelines. Its work supports high-priority commercial deliveries, including Nissan production and Robotaxi.

The role spans the model lifecycle, including data curation, model architecture and training, evaluation, deployment, and performance monitoring. It includes developing models that predict vehicle trajectories and interact with controllers and actuators, and using on-road and offline results to guide repeated, data-led improvement cycles. The team applies methods such as reinforcement learning, behavioural cloning, and distillation, with multi-sensor inputs such as cameras, radar, and lidar where relevant.

Wayve builds an end-to-end, mapless and hardware-agnostic AI platform for autonomous driving, designed to learn from real-world experience and support automation from L2+ through L4. The company operates a hybrid working model combining office collaboration and remote work. This is a high-ownership role in a growing team where processes are still being developed and the successful candidate can help shape how the team works.

Requirements

• Proven track record training deep learning models with clear end-to-end ownership of data, training, evaluation, and iteration.
• Experience taking ML models into production and working through real-world constraints, quality, and safety requirements.
• Strong Python skills and hands-on experience with modern ML frameworks.
• Experience shipping production-facing ML rather than working only on research or proof-of-concept projects.
• Background in either end-to-end autonomous driving/embodied AI or large-scale product ML systems such as recommendations or ranking.
• Reinforcement learning or behavioural cloning experience, especially where it materially improved real-world performance.

Nice To Haves

• Familiarity with model compression and deploying ML to embedded systems.
• Experience with multi-sensor inputs such as camera, radar, and lidar, where relevant.

Responsibilities

• Develop AI-driver model architectures and training algorithms to introduce and improve driving behaviours for L2/L3/L4.
• Own key parts of the training-model lifecycle, including evaluation strategy, success metrics, and iteration planning.
• Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviours, and implement data schemes to support training.
• Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.
• Build and improve models that predict vehicle trajectories and interact with controllers and actuators.
• Contribute across data, model training, evaluation, deployment, and performance monitoring.
• Use on-road and off-road metrics to diagnose issues and guide data-led model iterations.
• Build production-ready ML systems using strong software engineering, quality, and reliability practices.

Benefits

• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Hybrid working, core hours, and the opportunity to work hands-on in vehicle workshops and labs.
• Learning and development budgets, with support for training, conferences, and growth.
• Comprehensive benefits including health insurance, dental insurance, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, and wellbeing partner discounts.
• Salaries benchmarked against the market annually.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed