Lead Machine Learning Engineer

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 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.

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.

Essential 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.

Skills and Abilities

Success in this role typically requires the following competencies:

- 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.

Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

Required

- 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.