Senior Machine Learning Engineer, Driving Product

Overview

Join Wayve’s Driving Product team to build AI driver models that enable safe, scalable autonomous driving from L2 to L4. You will own end-to-end model development—from architecture and training to evaluation and on-road validation—shipping production-ready systems into vehicles. You’ll work across data, modeling, and deployment to improve real-world performance and safety. This is a fast-growing, high-ownership role with meaningful impact on commercial deployments and the future of autonomous mobility.

Pay / Benefits

• salary benchmarked annually
• meaningful equity
• relocation support and visa sponsorship
• hybrid working with core hours
• learning and development budgets
• comprehensive benefits including health and dental

Responsibilities

• Develop AI driver model architecture and training algorithms for L2/L3/L4 driving
• Own training lifecycle aspects: evaluation strategy, success metrics, iteration planning
• Curate real-world and synthetic data and implement data schemes for training
• Run and analyze on-road and offline experiments, defining next steps and retraining plans
• Build trajectory-prediction models that interact with controllers and actuators
• Perform end-to-end work across data, training, evaluation, deployment and monitoring
• Define on-road and off-road metrics to diagnose issues and guide data-driven iterations
• Deliver production-ready ML systems with solid software engineering practices
• Apply reinforcement learning, behavioural cloning, and distillation using multi-sensor inputs (camera, radar, lidar)

Key requirements

• Proven track record training deep learning models with end-to-end ownership
• Experience taking ML models into production with real-world constraints and safety requirements
• Strong Python skills and hands-on experience with modern ML frameworks
• Experience shipping production-facing ML beyond R&D
• Background in autonomous driving/embodied AI or large-scale product ML systems
• Experience with reinforcement learning or behavioural cloning that improved performance
• Familiar with model compression and deploying ML to embedded systems (nice to have)

• ownership
• data-driven decision making
• cross-functional collaboration
• Python
• PyTorch (including debugging)
• reinforcement learning

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