Staff Machine Learning Engineer, Robotics

Wayve is building the leading AI platform for autonomous driving through an end-to-end approach that enables vehicles to learn from real-world experience. The company's mapless, hardware-agnostic technology works with global OEM partners to enable continuous software evolution across autonomy levels. As the autonomous driving sector experiences significant growth—with AI and robotics roles expanding rapidly in a contracting overall job market—Wayve is expanding its engineering capacity to scale its technology across vehicle platforms.

The Vehicle Generalization Team at Wayve focuses on making the autonomous driving stack efficient and scalable across different vehicle platforms. This team improves how AI models generalize to changes in camera configuration, vehicle dynamics, and other platform differences, working directly with production programs from major OEMs. As a Staff Machine Learning Engineer on this team, you'll solve one of autonomous driving's core challenges: making models that work reliably across hardware variations.

What you'll do

• Design and train robust models using techniques like conditioning and augmentation to handle differences in vehicle kinematics, camera parameters, and sensor configurations across platforms.

• Build benchmarks and metrics that measure cross-platform performance, translating technical results into actionable decisions for model and platform teams.

• Debug on-road issues such as lane-keeping and steering problems by collaborating with controls, calibration, and OEM engineers to identify whether failures are model or system-related, then prioritize high-impact improvements.

• Move research solutions into production working alongside Driving Core and application engineering teams.

• Support customer programs, including some travel to vehicle test sites and OEM partners.

• Mentor team members and help establish higher standards for ML engineering practices across the organization.

What you'll bring

• Several years of experience building and shipping ML systems in PyTorch and Python, including training at scale, debugging experiments, and conducting rigorous evaluation.

• Strong background in robotics or automotive engineering, with expertise in areas like state estimation, sensor fusion, calibration, vehicle dynamics, or controls.

• Systems-level thinking that lets you trace problems from sensors through data, models, and actuation to identify root causes.

• Experience working with real-world, multi-sensor driving or robotics data in production contexts.

• Clear communication across teams and the ability to own ambiguous problems from definition through delivery.

Nice to have

• Experience with end-to-end learned driving policies, imitation learning, or reinforcement learning approaches.

• Background in multi-vehicle platform deployment or bring-up processes.

• C++ skills and experience with on-vehicle or embedded systems deployment.

What they offer

• Salaries benchmarked annually against market rates with meaningful equity.

• Hybrid working with access to vehicle workshops and labs.

• Relocation support and visa sponsorship where applicable.

• Comprehensive health, family, retirement, and wellbeing benefits.

• Learning and development support.