Principal Developer, AI Networking

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It is a unique legacy of innovation that has been fueled by great technology and amazing people. Today we are tapping into the unlimited potential of AI to define the next era of computing. In this era our GPU acts as the brains of computers, robots, and self‑driving cars that can understand the world.

Doing what has never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN you will be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are looking for a senior software engineer in the AI Networking Codesign and Benchmarking R&D group. In this role you will profile, analyze, and optimize AI workloads on large‑scale GPU and CPU clusters used for distributed deep‑learning LLM training and inference. Your primary focus will be collective communication and networking. You will work across hardware components such as HCAs, switches, CPUs, GPUs, and systems, and engage with software layers including LLM applications, machine‑learning frameworks, and communication and computing libraries.

You will also build performance analysis tools and strategies to investigate details, clarify performance expectations, limitations, and bottlenecks.

• Characterize AI workloads and deep‑learning models aimed at large‑scale LLM training and inference on NVIDIA supercomputers. The role centers on distributed systems with a focus on high‑performance networking and NVIDIA communication libraries.
• Benchmark, profile, and analyze performance to find bottlenecks and identify areas for improvement and optimization, with a strong emphasis on networking aspects.
• Develop a PyTorch trace‑based profiling, analysis, and replaying toolset to aid in benchmarking, debugging, and co‑designing network systems for LLM workloads.
• Collaborate with multiple teams from hardware to software to provide performance analysis insights.
• Define performance test plans, set performance expectations for new technologies and solutions, and work to achieve performance targets.

• 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 and the CUDA library. Knowledge of deep‑learning frameworks such as Tensor Flow or PyTorch. Expertise in networking collective communication libraries such as NCCL and protocols like RoCE and RDMA.
• Fast and self‑learning capabilities with strong analytical and problem‑solving skills.
• Proficiency in programming languages:
  Python, Bash, and C++.
• Experience with a container‑based development environment.
• Great teammate who communicates clearly and works well with others.

• Extensive understanding and hands‑on experience with AI workloads and benchmarking for distributed LLM training.
• Knowledge in PyTorch, CUDA, and NCCL libraries.
• Comprehensive system knowledge and understanding of Intel, AMD, and ARM CPUs, NVIDIA GPUs, HCA, memory, and PCI.
• Strong capabilities in performance evaluation and methods using contemporary tools.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD – 431,250 USD for Level 6, and 320,000 USD – 488,750 USD for Level 7. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and is proud to be an equal‑opportunity employer. We do not discriminate 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.