What is a Machine Learning Engineer at May Mobility?
At May Mobility, a Machine Learning Engineer plays a pivotal role in defining the future of autonomous transit. Unlike traditional automotive companies focusing solely on personal passenger vehicles, May Mobility designs and deploys autonomous micro-shuttles that integrate directly into municipal transit systems. This unique mission requires highly reliable, safety-critical machine learning systems capable of navigating complex urban environments. Your work will directly impact the safety, efficiency, and scalability of these autonomous fleets.
As part of the engineering team, you will tackle some of the most challenging problems in spatial computing, deep learning, and computer vision. Machine learning is embedded across the entire autonomy stack, but it is particularly critical in perception, prediction, and mapping. For those joining the mapping and routing teams, the focus is on automating the generation of high-definition (HD) maps, understanding lane-level connectivity, and building robust route networks. You will transform raw sensor data, including LiDAR, camera, and GPS trajectories, into highly structured, semantically rich graph networks that the vehicle's planner can query in real time.
This role is intellectually demanding and highly cross-functional. You will collaborate closely with software engineers, infrastructure specialists, and product managers to move models from research to production. At May Mobility, engineering is driven by a safety-first culture where code quality, deterministic fallbacks, and rigorous validation are just as important as model accuracy. If you are passionate about applying state-of-the-art deep learning to real-world physical systems, this role offers an unparalleled opportunity to see your models driving on public roads daily.
