Senior ML Engineer - Learned Localization

Design, build, and optimize ML models for localization, including learned pose estimation, map-matching, and sensor fusion pipelines using camera, LiDAR, and radar data. Develop high-performance training and evaluation workflows, leveraging PyTorch, distributed training, and large-scale datasets. Collaborate with robotics and mapping engineers to integrate localization models into the autonomy stack, ensuring real-time performance and stability. Analyze failure cases, run ablations, and improve model robustness through rigorous experimentation to achieve production-level reliability. Contribute to system design, code reviews, best practices, and documentation across ML and autonomy teams. Join a multidisciplinary group to deliver robust, real-time localization in challenging environments for autonomous trucking.