Senior/Staff Machine Learning Engineer, Sensor Simulation

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Nuro is developing a universal autonomy platform for Level 4 autonomous driving. The role involves researching and implementing synthetic sensor simulation methods using machine learning techniques such as NeRF and Gaussian splatting. You will work on generating photorealistic images and realistic lidar/radar data, analyzing sensor realism, and collaborating with cross-functional teams.

• Research, develop, and implement state-of-the-art synthetic sensor simulation methods. Analyze and characterize the realism and utility of synthetic sensor data. Answer critical questions about sensor data and autonomy performance. Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements.

• PhD in ML, CS, EE, robotics or related field with 3+ years, or Masters with 4+ years, or 5+ years industry experience. Deep understanding of ML fundamentals and hands-on training/evaluation of ML models. Strong Python skills with deep learning frameworks (PyTorch, TensorFlow, Jax).

• Deep understanding of 3D geometry and state estimation fundamentals. Proficiency in systems coding. Experience simulating/modeling real sensors (camera, lidar, radar, IMU) including noise modeling. Experience with NeRF, Gaussian Splatting, or generative models. Experience building ML pipelines and optimizing/productizing ML models. Research publications in top conferences (NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA).