Senior/Staff Machine Learning Engineer (Online Mapping)

• Our robotics team is growing and we are looking for an ML Software Engineer to join our Online Mapping team

• Building robust ML and/or mapping systems that work with real data (cameras, LiDAR, etc.) in uncertain environments, and a strong desire to contribute to the future of robot navigation for logistics and transportation

• Research, develop, and implement state-of-the-art online mapping models and algorithms

• Analyze and characterize the performance of the online mapping system, identifying opportunities for architecture, data or evaluation improvements in a E2E ML system

• Work cross functionally with other ML teams to integrate our models into centralized architectures

• Collaborate with stakeholders across autonomy, infrastructure, and systems teams on online mapping needs and requirements

Benefits

• Free Caltrain pass and commuter benefits

• Company stock options

• Work from home opportunities

• Health insurance- We are searching for an engineer with robotics and machine learning expertise to work on challenging problems in the design and implementation of onboard mapping models and algorithms, data and label management, as well as training pipelines

• Proven record of solving in-production ML problems and making tradeoffs between data, model and evaluation

• Strong Python skills with experience in deep learning frameworks, e.g., PyTorch, TensorFlow, or Jax

• Prioritize impact and practicality, and make decisions to ensure on-time delivery of solutions

• Able to quickly iterate and experiment to cut through the noise and make well-informed, data-driven decisions

• Deep understanding of ML fundamentals with hands-on experience in training and evaluating modern ML models with applications in AV, robotics, mapping, computer vision, or related areas

• Experience with robotics-related ML applications, 3D geometry

• Proficiency in working with complex multi-component systems

• Experience in building ML pipelines and optimizing/productizing ML models

• Familiarity with modern ML tools and infrastructure such as distributed training and ML compilers

• Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA)

• Deep understanding of 3D geometry and state estimation fundamentals