AI Engineer, Data Scaling & Optimization

• Design and implement high-performance neural network training infrastructure
• Optimize training and evaluation code for maximum efficiency
• Build data pipelines handling petabytes of autonomous vehicle and robotics data
• Develop profiling and debugging tools for ML training systems
• Implement distributed training across large GPU clusters
• Work with research teams to enable rapid experimentation at scale

• 4+ years experience with ML infrastructure and training systems
• Deep expertise in PyTorch or TensorFlow internals
• Strong understanding of distributed computing and GPU optimization
• Experience with large-scale data processing (petabyte+)
• Proficiency in Python and C++ for performance-critical code
• Knowledge of modern ML architectures (transformers, vision models)
• Experience optimizing memory usage and training throughput

Competitive salary and meaningful equity in the team building Fleet Learning Infrastructure for Physical AI

Full health, dental, and vision coverage, plus FSA and unlimited PTO

Work on the closed-loop data infrastructure that the next generation of autonomous systems learns from

A team that built Tesla Autopilot’s data infrastructure, now building something bigger #J-18808-Ljbffr