May Mobility

Senior Software Performance Engineer owning the latency, throughput, memory utilization, and thread safety of a real-time autonomous-vehicle decision-making pipeline. The role focuses on low-level C++ optimization, profiling, concurrency, and automated performance guardrails rather than autonomy-domain algorithms.

Lead Machine Learning Engineer responsible for advancing large-scale machine learning for May Mobility’s autonomous driving, simulation, and ML platform systems. The role combines hands-on model development with leadership of small teams working on VLA, world models, foundation models, and data-centric AI.

Lead the evolution of May Mobility’s autonomous-vehicle perception stack, from scene understanding and adverse-weather robustness to multimodal model integration. This hands-on technical leadership role combines robotics software architecture, machine learning, and production deployment in real-world vehicles.

Build the distributed data, training, and orchestration infrastructure that helps May Mobility continuously improve its autonomous-driving systems. This role combines machine learning, software engineering, cloud and cluster operations, and large-scale data pipelines.

Lead the next generation of production mapping and localization software for autonomous vehicles, using advanced ML and computer vision to model lane networks, road topology, and semantic features. You’ll own architecture, data strategy, model development, evaluation, and deployment across the vehicle fleet.

Lead the development of neural-network and mapping systems that give autonomous vehicles lane- and route-level spatial intelligence. You’ll own the mapping stack, data strategy, evaluation, and deployment while mentoring engineers and advancing production autonomy technology.

Join May Mobility as a Tech Lead in Performance Evaluation, where you'll leverage your expertise in data science and machine learning to enhance autonomous vehicle technology.