Senior/Staff Engineer, Machine Learning - Online Mapping

Nuro•Mountain View, CA

18d

About The Position

Nuro is seeking an ML Software Engineer to join their Online Mapping team. This role involves working on challenging problems in the design and implementation of onboard mapping models and algorithms, data and label management, and training pipelines. The ideal candidate will have expertise in robotics and machine learning, with a focus on building robust ML and mapping systems that operate with real-world data (cameras, LiDAR, etc.) in uncertain environments. The position contributes to the future of robot navigation for logistics and transportation.

Requirements

Proven record of solving in-production ML problems and making tradeoffs between data, model and evaluation.
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.
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.
Experience with robotics-related ML applications, 3D geometry.
Strong Python skills with experience in deep learning frameworks, e.g., PyTorch, TensorFlow, or Jax.

Nice To Haves

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.

Responsibilities

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.