Lead ML Engineer - Mapping
Core
Architecting and deploying production-grade semantic and topological mapping stacks to enable autonomous vehicles to navigate complex urban, suburban, and rural environments.
Role type
Lead ML Engineer (Autonomous Driving Mapping)
Builds
Production-grade lane and route network mapping stack, vectorized HD maps, and semantic features for AV navigation.
Domain
Autonomous driving, Computer Vision, Robotics
Deliverable
production ML models
Required skills
Computer Vision (object detection, segmentation, tracking, depth estimation, 3D reconstruction), Lane-level topology and graph construction, Vectorized mapping networks (MapTR), BEV-based scene representation, Self-supervised/semi-supervised learning, Foundation Models, PyTorch/TensorFlow, Python/C++, Distributed training, Data curation strategies, Linux-based development, Technical leadership and mentorship
Preferred skills
10+ years in AD/ADAS, Street-level and overhead imagery fusion, Vision-Language Models (VLMs), ML optimization (quantization, pruning), Top-tier conference publications
Technologies
PyTorch, TensorFlow, MapTR, Python, C++, Linux
Responsibilities
Architect and implement production-grade lane and route network mapping stacks; Lead research, design, training, and validation of advanced neural architectures for mapping; Drive feature development from inception to deployment; Own end-to-end data strategy including synthetic data and active learning; Develop robust metrics and evaluation frameworks for map accuracy; Collaborate with cross-functional teams to translate autonomy goals into software requirements; Stay at the research frontier by evaluating and innovating cutting-edge techniques like online vectorized HD map construction.
Seniority
Senior, hands-on IC with leadership responsibilities
