Senior/Staff Software Engineer, ML Performance Optimization (Autonomous Driving)

Location: Foster City, CA / Seattle, WA / Remote (United States)

Salary: $254,000–$350,000 per year

Company

Zoox is developing a fully autonomous vehicle fleet and the supporting ecosystem for mobility-as-a-service in urban environments.

What you will do

• Develop and execute the strategic vision for the ML Performance Optimization team.
• Design, implement, and operate ML training and inference performance optimization techniques for foundation models, VLMs, and VLAs.
• Scale models for efficient deployment in autonomous robotaxis using accelerators, distributed training, quantization, distillation, and pruning.
• Collaborate with ML researchers, software engineers, data engineers, and hardware engineers on requirements and architecture.
• Provide technical guidance and mentorship to help engineers grow.

Requirements

• Strong experience with PyTorch and efficient GPU usage for distributed model training.
• Experience with GPU-accelerated inference using TensorRT or similar frameworks.
• Experience with NVIDIA Nsight, PyTorch Profiler, or comparable profiling tools.
• Proficiency in Python and C++.
• Experience with model compression techniques for reducing model size and improving performance.
• Work is associated with Foster City, Seattle, or remote work within the United States.

Nice to have

• 10+ years of total experience, including 4+ years working on large-scale model training or inference platforms.
• Demonstrated ability to lead high-performing engineering teams.

Culture & Benefits

• Work at the intersection of robotics, machine learning, and design.
• Collaborate with autonomy teams including Perception, Prediction, Planner, Simulation, and Collision Avoidance.
• Contribute to the deployment of autonomous robotaxis on public roads.