Senior, ML Engineer - Learned Localization

Bachelor’s degree in Computer Science, Software Engineering, or related field with 6+ years of professional applied MLE engineering experience in Autonomous Vehicle, Robotics or related industry. Master’s degree in Computer Science, Software Engineering, or related field with 3+ years of professional applied MLE engineering experience in Autonomous Vehicle, Robotics or related industry. Experience with AV or robotics localization systems (e.g., LiDAR-based localization, visual odometry, SLAM, or map-based pose estimation). Strong experience developing and deploying ML models in perception, localization, or sensor fusion domains. Proficiency with PyTorch and modern ML tooling for training, inference, and optimization. Solid understanding of 3D geometry, probabilistic estimation, spatial transforms, and robotics fundamentals. Demonstrated ability to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation. Strong software engineering skills in Python or C++.

Design, build, and optimize ML models for localization, including learned pose estimation, map-matching, and sensor fusion pipelines. Develop high-performance training and evaluation workflows using PyTorch and distributed training infrastructure. Collaborate with robotics and mapping engineers to integrate localization models into the autonomy stack. Analyze failure cases, run ablations, improve model robustness, and drive rigorous experimentation. Contribute to system design, code reviews, best practices, and documentation.