Principal Machine Learning Engineer, Geometric Vision

Job description

Job responsibilities

• Design and train 3D foundation models and world models using large-scale driving data.
• Develop model architectures for 3D perception, geometric reasoning, reconstruction, and world modeling across space and time.
• Build scalable data generation and auto-labeling pipelines that produce high-quality geometric supervision from large volumes of sensor data.
• Develop and scale offline SLAM and 3D reconstruction systems and pipelines, using large-scale sensor data to recover accurate trajectories, scene geometry, calibration signals, and geometric supervision for model…
• Develop and apply techniques in multi-view geometry, neural rendering, NeRFs, Gaussian Splatting, implicit 3D representations, and feedforward 3D modeling.
• Explore geometry-aware tokenization and representation learning, including efficient ways to encode and fuse information across cameras, viewpoints, time, and sensing modalities.
• Develop foundation vision models that make effective use of camera, radar, LiDAR, and other sensor data for learning rich representations of the physical world.
• Explore video and generative modeling approaches for learning scene structure, dynamics, and future evolution from driving data.