Technical Staff Member for Physical AI
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Key Responsibilities
• Own model FLOPs utilization during video world model training
• Profile latency and GPU utilization for improved throughput
• Enhance precision and stability for video tokenizer and VAE layers
• Write and tune custom CUDA and Triton kernels
• Develop detection layer for silent data corruption issues
Requirements:
• Bachelor's degree or equivalent in a technical field
• Hands-on experience with PyTorch in multi-node jobs
• Fluency in Python and C++/CUDA programming
• Proficiency in profiling live training and inference runs
• Expertise in low-precision numerics or kernel authoring Drive innovation in Physical AI through expertise in PyTorch, distributed systems, and cutting-edge optimizations.
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