Lead Machine Learning Engineer

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

Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us.

🏢 About May Mobility

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.

🎯 The Role

As a Lead Machine Learning Engineer at May Mobility, you will be responsible for designing, training, and evaluating state-of-the-art models for our autonomous driving, simulation, and ML Platform stack. You will leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems. You will also lead small teams of cross-functional Engineers beyond the state of the art and define data balance, training experiment, and evaluation practices to train efficiently at petabyte scale.

✅ Key Responsibilities

• 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.

📌 Required Qualifications

• 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.

⭐ Desirable Experience

• 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.

🎁 Benefits

• Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate.
• Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
• Rich retirement benefits, including an immediately vested employer safe harbor match.
• Generous paid parental leave as well as a phased return to work.
• Flexible vacation policy in addition to paid company holidays.
• Total Wellness Program providing numerous resources for overall wellbeing

🛂 Visa & Eligibility

May Mobility is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis.