Lead Machine Learning Engineer - Modeling

About the role

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology. Our vehicles provide value to communities, bridge public transit gaps, and move people safely and efficiently. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access, and fostering vibrant, livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides globally.

We’re hiring Machine Learning Leaders to enhance May’s Machine Learning capabilities both on and off the vehicle in a commercial large-scale environment with high standards of quality.

Responsibilities

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

Requirements

• Direct experience architecting and 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.

Qualifications

• Extensive practical experience in one of the following domains: Vision Language Action Models, Generative World Models, or Foundation Models in Robotics.
• 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 requiring 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.

Desirable Qualifications

• 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.

Physical Requirements

• Prolonged sitting, standing, and computer use in a standard office environment.
• Low travel required (5%-10%).