Machine Learning Engineer (Simulation)

TL;DR

Machine Learning Engineer (Simulation): Developing and optimizing GPU-based simulation frameworks for autonomous vehicle validation with an accent on reinforcement learning and bridging sim-to-real fidelity gaps. Focus on building scalable data generation systems and integrating advanced ML algorithms into core simulation architecture.

Location: Must be based in or able to work from Foster City, CA or Seattle, WA (Hybrid)

Company

Zoox is an autonomous vehicle company creating advanced robotics and AI solutions for the future of transportation.

What you will do

• Develop and optimize GPU-based simulation frameworks to support complex ML training and validation pipelines.
• Apply reinforcement learning concepts to solve behavioral and path planning challenges.
• Identify and resolve sim-to-sim and sim-to-real fidelity gaps to ensure parity with physical vehicle execution.
• Build self-service data generation systems for autonomy users to accelerate training iterations.
• Write production-ready code to integrate advanced ML algorithms into core simulation architecture.

Requirements

• PhD or Master’s degree in computer science, robotics, machine learning, or related field.
• Deep understanding of reinforcement learning in simulated or robotic environments.
• Hands-on experience with deep learning frameworks such as JAX or PyTorch.
• Strong proficiency in C++ and Python for production systems.
• Experience analyzing and bridging fidelity gaps between synthetic data and real-world execution.

Nice to have

• Experience with GPU programming (CUDA) or high-performance compute clusters.
• Background in the automotive or autonomous robotics industry.
• Experience with deterministic systems and latency optimization.

Culture & Benefits

• Comprehensive health, long-term care, and disability insurance.
• Competitive compensation including salary, Amazon RSUs, and Zoox Stock Appreciation Rights.
• Paid time off including vacation, sick leave, and bereavement.
• Commitment to diverse perspectives and inclusive team building.