Staff Machine Learning Engineer, Robotics

About the role

Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here’s what this particular role covers.

About the Vehicle Generalization Team

Vehicle Generalization makes it efficient, scalable, and predictable to deploy Wayve’s autonomous driving stack across a wide range of vehicle platforms by making our core autonomy generalise as widely as possible.

We work across pre- and post-training to improve how well our AI models generalise zero-shot to changes in perception-including cameras, intrinsics, field of view, lens distortion, and calibration-and embodiment, including vehicle dynamics, actuation limits, and rig geometry. We also own the Generalization Benchmark, Wayve’s tool for measuring how models transfer across platforms. Our work goes into production programmes with major OEMs.

We’re looking for a hands-on Machine Learning Engineer with a strong robotics background who understands how a real vehicle senses, estimates its state, and moves. You’ll identify where our models break down across platforms, understand why, and address those failures in training-then prove the improvement through rigorous evaluation.

Your Day-to-day

• 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, translating results into clear decisions for model and platform teams.
• Help root-cause on-road issues such as late turns, lane-keeping, and steering problems. Work with controls, calibration, and OEM engineers to separate model problems from system problems and identify the highest-impact model improvements.
• Move research into production in collaboration with Driving Core and application engineering teams.
• Support customer programmes, with some travel.
• Mentor teammates and help raise the bar for ML engineering across the team.

What You’ll Be Working on

• Pre- and post-training methods that improve zero-shot transfer across vehicle platforms.
• Robustness to changes in camera configuration, calibration, vehicle dynamics, actuation limits, and rig geometry.
• The Generalization Benchmark and metrics that measure how models transfer between platforms.
• Real-world, multi-sensor driving data and the interaction between sensors, data, models, and actuation.
• Production deployment of Wayve’s autonomy stack with major OEM partners.

You Should Apply If

• You have several years of experience building and shipping ML systems in PyTorch and Python, including training at scale, debugging experiments, and rigorous evaluation.
• You have a strong robotics or automotive background in areas such as state estimation, sensor fusion, calibration, vehicle dynamics, or controls.
• You bring a systems perspective and can trace a problem through sensors, data, models, and actuation.
• You have experience working with real-world, multi-sensor driving or robot data.
• You communicate clearly across teams and are comfortable owning ambiguous problems from start to finish.

Nice to Have

• 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.

Additional information

Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More About Wayve

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience, developing the ability to adapt, generalise and improve at scale.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware-agnostic AI platform integrates with global OEM partners, enabling continuous software evolution from L2+ through to L4.

How We Work - Locations & Flexible Working

This role is based in Sunnyvale, CA (preferred), or London. We operate a hybrid model that combines in-person collaboration with focused time working remotely. Some travel is required to support customer programmes.

The Interview Process

• Initial call / recruiter screen - 25 minutes
• Hiring-manager discussion - 45 minutes
• Deep-dive technical interviews - approximately 4 hours total
• Final interview focused on mission and values alignment - 1 hour

We’ll always explain the format and work around your availability.

What’s in IT for You (Location Dependent)

• Salaries benchmarked against the market annually
• 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

A quick, honest note before you apply.

• Wayve is not a mature, fully-structured place with the playbook already written.
• Much of how we work is still being written, and if you join, you’ll help write it.
• That suits people who want real ownership more than people who need a settled structure from day one.

• If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.
• For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve