Lead Machine Learning Engineer

Overview

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 Multi-Policy Decision Making (MPDM) technology that reimagines the way AVs think.

Our vehicles provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with more convenience. We are building the world s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster greener, more vibrant and livable spaces. Since our founding in 2017, we have given more than 500,000 autonomous rides to real people around the globe.

We are hiring people who share our passion for building the future, solving real-world problems, and seeing the impact of their work. Join us.

Salary Range
: $220,000—$270,000 USD

• 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 experiments and evaluation practices to train efficiently at petabyte scale.

• Extensive practical experience in one of the following domains:
• Vision Language Action Models
• Generative World Models
• Foundation Models in Robotics
• Data Centric AI
• 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.
• Familiar with common post-training techniques.
• Experience deploying models to resource constrained and edge hardware
• Functional understanding of C/C++/CUDA memory and threading models.

• Standard office working conditions including prolonged sitting, standing, and computer use.
• Travel:
  Low (5%–10%).

• Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have resided together at least one year are also eligible to participate.
• Health Savings and Flexible Spending Accounts available.
• Retirement benefits with employer matching.
• Paid parental leave and phased return to work.
• Flexible vacation policy in addition to paid company holidays.
• Wellness program with resources for overall wellbeing.