Lead ML Engineer (VLA/ALM focused)
May Mobility is seeking a Lead Machine Learning Engineer with a focus on Vision-Language Models (VLMs) and Autonomous Learning Machines (ALMs) to join our team in Ann Arbor, Michigan. As a pioneer in autonomous vehicle technology, May Mobility is dedicated to transforming urban transportation through innovative solutions. This role offers the opportunity to contribute to the development of cutting-edge perception systems that enhance the safety and efficiency of our autonomous shuttles.
In this position, you will collaborate with cross-functional teams to define software and system requirements, design and implement advanced perception features, and integrate VLMs and ALMs into our perception stack. Your responsibilities will include leading major feature developments, conducting extensive testing to validate features, and developing data and machine learning pipelines focused on multimodal data alignment for training foundation models.
The ideal candidate will possess a minimum of 5 years of industry experience working on real-world robotic systems, maintaining high-quality, industrial-grade code. A Master's degree in Robotics, Computer Science, or a related field is required. Strong programming skills in C/C++/Python, experience with ML/DL development using PyTorch or TensorFlow, and direct experience developing or fine-tuning VLMs for real-world applications are essential. Experience in areas such as computer vision, semantic scene understanding, multi-target tracking, and sensor fusion is also highly valued.
May Mobility offers a comprehensive benefits package, including medical, dental, vision, life, and disability plans, as well as health savings and flexible spending accounts. We provide rich retirement benefits with an immediately vested employer safe harbor match, generous paid parental leave, a flexible vacation policy, and a total wellness program to support overall well-being.
Joining May Mobility means becoming part of a team that is passionate about building the future of transportation today. We value solving real-world problems and seeing the tangible impact of our work. Our culture fosters innovation, collaboration, and continuous learning, offering growth opportunities for those eager to make a difference in the autonomous vehicle industry.