data
Posted Apr 24Lead ML Engineer - Lane & Route Networking Mapping
at May Mobility
On-site
Responsibilities
- Lead the research, design, architecture, training and validation of advanced neural networks for vectorized mapping (e.g., MapTR), multi-camera BEV transformers, and multimodal fusion models to extract and model lane and route networks for both high-fidelity offline pipelines and real-time online mapping.
- Architect, design, and implement a production-grade lane and route network mapping stack, ensuring high-performance integration with upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
- Drive major feature development from inception to deployment.
- Own the end-to-end data strategy for the mapping domain, specifically focusing on lane and route networks.
- Develop robust metrics and evaluation frameworks for lane and route network accuracy, temporal consistency, and scaling across diverse Operational Design Domains (ODDs).
- Collaborate with ML and Autonomy engineers to ensure the seamless deployment and validation of mapping features to the vehicle fleet.
Requirements
- 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.
- Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation.
- experience developing and deploying ML/DL models for mapping or computer vision at scale.
- Vectorized mapping networks (e.g., MapTR), BEV-based scene representation, and temporal modeling.
- Strong understanding of HD maps, including lane and road network geometry modeling, connectivity, and semantic attributes.
- Expertise in ML/DL development using PyTorch or TensorFlow, including
- experience with distributed training, synthetic data generation, large-scale dataset handling, and data curation strategies.
- Strong programming skills in Python and/or C++ with
- experience in modular software design and Linux-based development.
- experience in ML/DL for autonomous driving or ADAS systems. •
- Experience with self-supervised and/or semi-supervised learning for large-scale representation learning. •