Nvidia Senior Network Software Engineer 

United States, Texas 

961985739

hat you will be doing:

• Collaborate with multi-functional teams to analyze, co-design, and develop networking software and hardware for innovative AI platforms.

• Drive the development of new networking algorithms and protocols for point-to-point and collective operations at scale.

• Identify bottlenecks and inefficiencies in application code, proposing optimizations to enhance performance and network utilization.

• Design and implement performance benchmarks and testing methodologies to evaluate performance at scale.

• Provide guidance and recommendations for optimizing AI applications for speed, scalability, and resource efficiency.

• Share knowledge with domain expert teams as they develop applications for the next generation of AI platforms.

• Contribute to the development of tools and frameworks to facilitate network optimization.

What We Need to See​:

• PhD in Computer Science, Computer Engineering, or related field, or equivalent experience

• 10+ years of experience with a focus on high-performance networking and AI applications

• Expertise in RDMA networking (InfiniBand, ROCE), Ethernet, and PCIe.

• Experience with at least one high-performance networking library: NCCL, UCX, libfabric, MPI, UCC.

• Deep understanding of various aspects of high-performance networking, including network technologies, debugging, and performance analysis.

• Experience in developing and optimizing deep learning frameworks such as PyTorch and TensorFlow.

• Proficiency in Python and C/C++.

• Experience in CUDA programming.

• Track record of delivering performance improvements for software used in large-scale deployments.

• Knowledge of Kubernetes (k8s) and cloud-native application principles is a plus.

• Familiarity with continuous integration and delivery practices for performance optimization.

Ways To stand out from the crowd:

• Hands-on experience in optimizing networking building blocks for DL frameworks like PyTorch and TensorFlow.

• Experience in developing communication libraries such as NCCL, UCX, UCC, MPI.

• In-depth knowledge of RDMA, GPU-Direct, and network technologies.

• Provide references to your code contributions.