Principal Developer, AI Networking

Job Summary

Focusing on profiling, analyzing, and optimizing AI workloads on large-scale GPU and CPU clusters, the full-time Principal Developer, AI Networking will work remotely or onsite to enhance distributed Deep Learning LLM training and inference, with an emphasis on networking and performance analysis.

Key responsibilities

• Characterizing AI workloads and deep learning models for large-scale LLM training and inference on NVIDIA supercomputers
• Benchmarking, profiling, and analyzing performance to identify bottlenecks and optimization opportunities, particularly in networking
• Developing tools for PyTorch trace-based profiling and collaborating with cross-functional teams to provide performance analysis insights

Required qualifications

• B.Sc in Computer Science or Software Engineering or equivalent experience
• 15+ years of experience with high-performance networking (RDMA, MPI, NCCL, SHARP)
• Demonstrated ability in performance evaluation techniques and approaches
• Experience with NVIDIA GPUs, the CUDA library, and deep learning frameworks like TensorFlow or PyTorch
• Proficiency in programming languages: Python, Bash, and C++