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SeniorFull-timePythonC++Machine LearningPyTorch
Salary Range
$242,000 - $290,000 /year
About the Role
The Perception team at Zoox is responsible for the robot’s understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks.
Key Responsibilities
- →Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow
- →Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities
- →Engineer temporal processing modules to improve the stability and consistency of predictions over time
- →Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints
- →Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering
Requirements
- ✓MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience
- ✓Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures
- ✓Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration
- ✓Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences
- ✓Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation
