Lead Machine Learning Engineer

What you'll do

• Design, train, and evaluate models for autonomous driving, simulation, and the ML platform.
• Apply emerging End-to-End driving, VLA, World Model, or Foundation Model techniques to commercial-scale problems.
• Lead small cross-functional engineering teams and define data, training, and evaluation practices for petabyte-scale work.

What they ask for

• At least 4 years of industry experience working on commercial robotics systems and at least 1 year mentoring ML Engineers in a commercial or lab environment.
• Extensive practical experience in Vision Language Action Models, Generative World Models, Foundation Models in Robotics, or Data Centric AI; practical experience addressing the long-tail problem in Machine Learning.
• Master’s degree in Robotics, Computer Science, Computer Engineering, or a field requiring a strong mathematical and/or engineering foundation.
• Strong programming skills in Python/PyTorch in a Linux environment; functional understanding of LiDAR, Camera, and Radar processing techniques.

Nice to have

• PhD and/or published research in the described specialty domains; familiarity with common post-training techniques.
• Experience deploying models to resource-constrained and edge hardware; functional understanding of C/C++/CUDA memory and threading models.

Pay

$220,000 — $270,000 USD (base salary)

Tools

Python, PyTorch, Linux, LiDAR, Camera, Radar, C/C++, CUDA

AI focus

Develops models for autonomous driving, simulation, and ML platforms, including VLA, Generative World, and Foundation Models; addresses long-tail failures and scales data, training, and evaluation.