Description
Join NVIDIA's Cosmos Lab Infrastructure team to develop training and post-training systems for advanced Physical AI models. You will work on implementing and evaluating systems improvements on real AI workloads using NVIDIA's GPU infrastructure.
Responsibilities:
- Develop and optimize training infrastructure for advanced Physical AI world models
- Build Physical AI post-training and RL infrastructure supporting advanced training algorithms
- Improve efficiency and scalability across training, inference, simulation, and evaluation
- Analyze and optimize system performance, working with researchers to investigate emerging Physical AI models
Requirements:
- Pursuing a Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field
- Strong Python and debugging skills, with systems fundamentals in concurrency, distributed execution, memory management, or data movement
- Practical experience in at least one area: training infrastructure, RL infrastructure, simulation or robotics integration, or inference infrastructure
- Strong analytical and communication skills, curiosity, and a willingness to learn
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