Develop machine learning algorithms for Bird’s Eye View scene analysis and real-time hazard detection.
Design and implement scene understanding solutions specifically for Zoox's unique bidirectional vehicle.
Lead the end-to-end data strategy—including mining, auto-labeling, and dataset construction—to keep our ML models improving.
Implement on-vehicle software for model inference and result post-processing that runs reliably in real-time.
Use our large-scale data pipelines and infra to research, prototype, and deploy changes that directly improve how the vehicle handles complex road scenarios.
Team up with Perception, Prediction, and Planning teams to integrate your signals into the final driving solution.

Requirements

BS, MS, or PhD in Computer Science, Robotics, or a related field with 2+ years of industry experience training and deploying ML models.
Experience with BEV (Bird’s Eye View) models, segmentation, or 3D representations.
Hands-on experience with the full lifecycle: dataset construction, training frameworks, and building metrics pipelines to evaluate performance.
A strong mathematical foundation in linear algebra, calculus, and probability.
Fluency in C++ and Python. Experience with PyTorch, TensorFlow, JAX.

Benefits

Applicant Tracking System Keywords

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

machine learning algorithmsscene analysishazard detectiondataset constructionmodel inferencereal-time processingdata pipelinesC++PythonPyTorch

leadershipteam collaboration