Senior ML Engineer - Mapping

The Autonomy Mapping & Localization group's mission is to provide our vehicles with world-class spatial intelligence, semantic and topological mapping, and state estimation to model and navigate complex urban, suburban, and rural environments. We are looking for a Senior ML Engineer to join our team and build  the next generation of our mapping and localization stack. As the Senior ML Engineer for Mapping, you will be at the forefront of this mission, building the production-grade semantic and topological foundation that allows our vehicles to understand and navigate the world's most challenging roads at scale.

• →Implement and optimize production-grade lane and route network mapping ML, ensuring high-performance integration with the broader autonomy system.
• →Research, train, and evaluate advanced neural architectures. This includes object detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction to extract and model lane and route networks, alongside key semantic features (e.g., traffic signs, signals, and road markings), for automated mapping.
• →Participate in rigorous code reviews, automated testing, and technical resolution.
• →Develop data curation,  auto-labeling, and active learning pipelines. 
• →Develop evaluation scripts for lane and route network accuracy, 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.

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

• Standard office working conditions which includes but is not limited to:
• Prolonged sitting
• Prolonged standing
• Prolonged computer use
• Travel required? - Low: 5%-10%

• M.S. or Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation.
• 5+ years of industry experience developing and deploying ML/DL models for mapping or computer vision at scale.
• Deep expertise in several  of the following areas:
• Computer Vision Foundations: Object detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction.
• Lane-level topology and connectivity, intersection modeling, and lane/road network graph construction.
• Vectorized mapping networks (e.g., MapTR), BEV-based scene representation, and temporal modeling.
• Self-supervised/semi-supervised and vision/fusion Foundation Models.
• Expertise in ML/DL development using PyTorch or TensorFlow, including experience with synthetic data generation, data curation, and model/algorithm evaluations.
• Strong programming skills in Python and/or C++ with experience in modular software design and Linux-based development.

• Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation.
• Strong understanding of HD maps, including lane and road network geometry modeling, connectivity, and semantic attributes.
• Experience with feature extraction and/or fusion from both street-level and overhead imagery.
• Expertise in ML optimization for real-time products with limited compute, such as quantization and pruning of large transformer models.
• A proven record of inventions and/or publication record at top-tier conferences (e.g., CVPR, NeurIPS, ICCV, ECCV, ICLR).