Requirements:

B.Sc in Computer Science or Software Engineering
6+ years of experience with high-performance Networking (RDMA, MPI, NCCL)
Demonstrated Performance Analysis skills and methodologies
Experience with NVIDIA GPUs, CUDA library, deep learning frameworks like TensorFlow or PyTorch
Combined with expertise in networking collective communication libraries (such as NCCL) and protocols (such as RoCE and RDMA)
Fast and self-learning capabilities with strong analytical and problem-solving skills
Programming Languages: Python, Bash, and C languages
Experience with Linux OS distros
Team player with good communication and interpersonal skills

Nice to haves:

In-depth knowledge and experience with AI workloads benchmarking for distributed LLM training, CUDA, and NCCL libraries
In-depth System knowledge and understanding (Intel / AMD / ARM CPUs, NVIDIA GPUs, HCA, Memory, PCI)
Knowledge in Congestion Control algorithms

Experience and research AI workloads and DL models tailored for large-scale deep learning LLM training on NVIDIA supercomputers with a focus on High-performance networking
Benchmarking, Profiling, and Analyzing the performance to find bottlenecks and identify areas of improvement and optimizations, with a strong emphasis on networking aspects
Implement performance analysis tools
Collaborating with many teams from HW to SW to provide performance analysis insights
Define performance test planning, set performance expectations for new technologies and solutions, and work to reach the performance targets limits

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer
No discrimination on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law