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Lead Machine Learning Engineer (VLA/ALM Focused)

May MobilityAnn Arbor, MI
On-site Full-time $200K/yr - $240K/yr

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Experience Level

Manager

Qualifications

We are seeking candidates with a robust understanding of machine learning, particularly in perception systems for autonomous vehicles. Ideal candidates will have experience with VLMs and LLMs and possess strong programming skills in relevant languages, such as Python and C++. A Master’s degree in a related field is preferred, along with a proven track record of delivering high-quality software solutions in complex environments.

About the job

May Mobility builds autonomous vehicle technology in Ann Arbor, Michigan, focused on making urban transportation safer and more accessible. Since 2017, the team has delivered over 500,000 autonomous rides worldwide, using proprietary Multi-Policy Decision Making (MPDM) systems. The company’s AVs support public transit, reduce congestion, and promote sustainable city living.

Role Overview

The Lead Machine Learning Engineer (VLA/ALM Focused) will join the robotics engineering group as May Mobility expands its autonomous shuttle and mobility services. The role centers on advancing perception systems, particularly by integrating Vision-Language Models (VLMs) and Large Language Models (LLMs) to improve how vehicles interpret and respond to their environment.

What You Will Do

  • Work closely with cross-functional teams to define and develop software and system requirements.
  • Design, implement, and test advanced perception features, ensuring they meet high-quality and production standards.
  • Integrate VLMs and LLMs into the perception framework to boost semantic scene understanding and reasoning.
  • Monitor and analyze perception system performance using real-world data.
  • Lead development of major features that advance May Mobility’s perception technology.

Location

This position is based in Ann Arbor, MI.

About May Mobility

May Mobility is pioneering the future of transportation by developing autonomous vehicles that not only drive themselves but also contribute positively to the communities they serve. Our innovative technology and commitment to sustainability are reshaping public transit and enhancing the urban experience for everyone.

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