Staff Machine Learning Engineer, Robotics

Wayve • Sunnyvale, CA

6d • $370,040 - $419,760 • Hybrid

About The Position

Wayve’s Vehicle Generalization Team helps deploy its autonomous driving stack efficiently, scalably, and predictably across a wide range of vehicle platforms. The team works across pre- and post-training to improve how AI models generalize to changes in perception—such as cameras, intrinsics, field of view, lens distortion, and calibration—and embodiment, including vehicle dynamics, actuation limits, and rig geometry. It also owns the Generalization Benchmark, which measures how models transfer across platforms, and supports production programmes with major OEMs.

This hands-on role combines machine learning engineering and robotics. You will identify where models break down across vehicle platforms, investigate the causes, address failures through training, and rigorously evaluate the results. The work spans real-world, multi-sensor driving data; model robustness and benchmarking; on-road issue investigation; and production deployment with OEM partners. The role is based in Sunnyvale, California (preferred), or London, and follows a hybrid working model. Some travel is required to support customer programmes.

Requirements

• Several years of experience building and shipping ML systems in PyTorch and Python, including training at scale, debugging experiments, and rigorous evaluation.
• A strong robotics or automotive background in areas such as state estimation, sensor fusion, calibration, vehicle dynamics, or controls.
• A systems perspective and ability to trace problems through sensors, data, models, and actuation.
• Experience working with real-world, multi-sensor driving or robot data.
• Clear communication across teams and comfort owning ambiguous problems from start to finish.

Nice To Haves

• Experience with end-to-end or learned driving and planning policies, imitation learning, or reinforcement learning.
• Experience with platform bring-up or deployment across multiple vehicles.
• C++ skills and experience with on-vehicle or embedded deployment.

Responsibilities

• Design and train models that are robust to differences between vehicles, using approaches such as conditioning or augmentation for vehicle kinematics and camera parameters.
• Create benchmarks and metrics for cross-platform performance and translate results into clear decisions for model and platform teams.
• Help root-cause on-road issues, including late turns, lane-keeping, and steering problems, working with controls, calibration, and OEM engineers to distinguish model issues from system issues and identify high-impact model improvements.
• Move research into production in collaboration with Driving Core and application engineering teams.
• Support customer programmes, including some travel.
• Mentor teammates and help raise the bar for ML engineering across the team.

Benefits

• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Hybrid working and access to vehicle workshops and labs.
• Learning and development support.
• Comprehensive location-dependent health, family, retirement, and wellbeing benefits.
• Salaries benchmarked against the market annually.

What This Job Offers

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