Zoox

In this role, you will:

• Develop and optimize our GPU-based simulation framework to support complex machine learning training and validation pipelines.
• Apply reinforcement learning concepts to solve complex behavioral and path planning challenges in simulation environments.
• Identify and resolve "sim-to-sim" and “sim-to-real” fidelity gaps to ensure parity between high-speed ML simulations, high-fidelity 3D environments, and physical vehicle execution.
• Build systems that allow autonomy users to self-serve data generation and accelerate their training iterations.
• Write robust, production-ready code to integrate advanced ML algorithms directly into our core simulation architecture.

Qualifications:

• PhD or Master’s in computer science, robotics, machine learning, or a related field.
• Deep understanding of reinforcement learning and its application in simulated or robotic environments.
• Hands-on experience developing, training, and fine-tuning deep learning models using modern frameworks (e.g., JAX or PyTorch).
• Strong proficiency in C++ and Python for building and deploying production machine learning systems.
• Experience analyzing and bridging fidelity gaps between synthetic training data and real-world execution.

Bonus Qualifications:

• Experience with GPU programming (CUDA) or high-performance compute clusters.
• Automotive or autonomous robotics industry experience.
• Strong background in deterministic systems and latency optimization.

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations

If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note:

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.