Contribute to the development of next-generation 3D occupancy and segmentation networks
Architect and optimize high-performance deep learning models for dense, temporally consistent voxel representations
Enable vehicle navigation in complex urban scenarios by providing precise geometry and motion estimates

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.

Benefits

paid time off (e.g. sick leave, vacation, bereavement)
unpaid time off
Zoox Stock Appreciation Rights
Amazon RSUs
health insurance
long-term care insurance
long-term and short-term disability insurance
life insurance

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

3D Computer VisionDeep LearningVoxel-based architecturesBEV (Bird's Eye View) architecturesPythonPyTorchC++Multi-sensor fusionTemporal data sequencesOccupancy networks

Certifications

MS in Computer SciencePhD in Computer ScienceMS in RoboticsPhD in RoboticsMS in Machine LearningPhD in Machine Learning