Software Engineer, Machine Learning, Sensor Simulation
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The role
Design, research, and implement state-of-the-art synthetic sensor simulation methods to generate photorealistic images and realistic LiDAR/Radar data for autonomous perception systems.
Train and evaluate machine learning models (e.g., NeRF, Gaussian splatting) and analyze the realism and utility of generated data for downstream tasks.
Model cameras, LiDAR, radar, IMU and their noise characteristics, while incorporating 3D geometry and state estimation fundamentals.
Collaborate with cross-functional teams on map requirements and data needs to support autonomy and infrastructure workstreams.
Build robust ML pipelines, optimize models for production, and contribute to tooling for scalable synthetic data generation.
Stay at the forefront of graphics ML techniques and publish insights when applicable.
Train and evaluate machine learning models (e.g., NeRF, Gaussian splatting) and analyze the realism and utility of generated data for downstream tasks.
Model cameras, LiDAR, radar, IMU and their noise characteristics, while incorporating 3D geometry and state estimation fundamentals.
Collaborate with cross-functional teams on map requirements and data needs to support autonomy and infrastructure workstreams.
Build robust ML pipelines, optimize models for production, and contribute to tooling for scalable synthetic data generation.
Stay at the forefront of graphics ML techniques and publish insights when applicable.
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