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NVIDIA AI in Austin is seeking an experienced ML engineering professional to develop and optimize accelerated PyTorch-based solutions for large-scale models on GPU infrastructure.
You will collaborate with cross-functional teams, support CUDA-X libraries, and influence product priorities based on customer technical requirements. A strong background in C++, PyTorch, and GPU-accelerated development is essential.
Develop and optimize accelerated PyTorch-based solutions for large-scale machine learning models, including GNNs and ensemble models on GPU infrastructure. Collaborate with cross-functional teams to support CUDA-X libraries and guide product priorities based on customer technical requirements.
Requires a Bachelor's degree with 5+ years of experience or a Master's/PhD with 3+ years in machine learning and data science. Candidates must possess strong C++ skills, extensive experience with PyTorch, and a proven track record in GPU-accelerated application development.
PyTorch, C++, CUDA, Graph Neural Networks, Machine Learning, Deep Learning, GPU Acceleration, Distributed Infrastructure, Data Science, Performance Optimization, Software Design, System Architecture, PyTorch Geometric, Profiling, Orchestration
Equity, Benefits