Lead Machine Learning Engineer

We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May’s Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality.

• Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack.

• Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.

• Lead small teams of cross functional Engineers beyond the state of the art.

• Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.

• Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial-scale applications

• Experience composing, processing and characterizing large (>100TB) multi-modal datasets

• Experience analyzing and addressing long-tail failure cases in large models

• Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership.

• Extensive practical experience in one of the following domains:

• A minimum of 4 years of industry experience working on commercial robotics systems.

• A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.

• Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.

• Practical experience handling the “Long Tail” problem in Machine Learning.

• Strong programming skills in Python/PyTorch in a Linux environment.

• Functional understanding of LiDAR, Camera and Radar processing techniques.

• PhD and/or published research in the described specialty domains.

• Experience deploying models to resource constrained and edge hardware

• Functional understanding of C/C++/CUDA memory and threading models.