Senior Deep Learning Communication Architect

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a senior- or staff-level engineer in Santa Clara to advance distributed deep learning communication, parallelism, and high-speed interconnects. You will partner with hardware and software teams to optimize DNN training and inference across state-of-the-art GPUs.

You will work with cutting-edge frameworks (PyTorch, TensorRT-LLM, vLLM) and explore new serving architectures, delivering proofs-of-concept and scalable solutions.

Qualifications

• PhD, Masters, or BS in CS, EE, CSEE, or closely related field, or equivalent experience.
• 6+ years building DNNs, scaling DNNs, parallelism, or DL training/inference workloads.
• Experience evaluating and optimizing LLM training and inference performance on cutting-edge hardware.
• Deep understanding of Data, Pipeline, Tensor, Expert, and FSDP parallelism techniques.
• Familiarity with serving architectures (Disaggregated Serving) and inference servers (Dynamo, Triton).
• Proficiency in developing code for DNN frameworks (e.g., PyTorch, TensorRT-LLM, vLLM, SGLang).
• Strong programming skills in C++ and Python.
• Familiarity with GPU computing (CUDA/OpenCL) and networks (InfiniBand, RoCE).

Responsibilities

• Optimize communication performance in distributed DL training and inference.
• Design efficient communication protocols for DL workloads.
• Collaborate with hardware and software teams to leverage high-speed interconnects (NVLink, InfiniBand).
• Develop and evaluate new communication technologies for scalable DL systems.
• Build proofs-of-concept, run experiments, and model quantitatively to deploy new strategies.

Skills

C++

Python

Data Parallelism

Education

PhD/Masters/Bachelor's in CS/EE/CSEE

Tools

CUDA

OpenCL

InfiniBand

RoCE

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll 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.

What You'll Be Doing:

• Optimizing communication performance: Identify and eliminate bottlenecks in data transfer and synchronization during distributed deep learning training and inference.
• Designing efficient communication protocols: Develop and implement communication algorithms and protocols tailored for deep learning workloads, minimizing communication overhead and latency.
• Hardware and software co-craft: Collaborate with hardware and software teams to craft systems that effectively apply high-speed interconnects (e.g., NVLink, InfiniBand, SPC-X) and communication libraries (e.g., MPI, NCCL, UCX, UCC, NVSHMEM).
• Exploring innovative communication technologies: Research and evaluate new communication technologies and techniques to enhance the performance and scalability of deep learning systems.
• Developing and implementing solutions: Build proofs-of-concept, conduct experiments, and perform quantitative modeling to validate and deploy new communication strategies.

What We Need to See:

• A Ph.D., Masters, or BS in Computer Science (CS), Electrical Engineering (EE), Computer Science and Electrical Engineering (CSEE), or a closely related field or equivalent experience.
• 6+ years of experience in Building DNNs, Scaling of DNNs, Parallelism of DNN frameworks, or deep learning training and inference workloads.
• Experience in evaluating, analyzing, and optimizing LLM training and inference performance of state-of-the-art models on cutting-edge hardware.
• Deep understanding of parallelism techniques, including Data Parallelism, Pipeline Parallelism, Tensor Parallelism, Expert Parallelism, and FSDP.
• Understanding of the emerging serving architectures like Disaggregated Serving and inference servers like Dynamo and Triton Proficiency in developing code for one or more deep neural network (DNN) training and Inference frameworks, such as PyTorch, TensorRT-LLM, vLLM, SGLang.
• Strong programming skills in C++ and Python.
• Familiarity with GPU computing, including CUDA and OpenCL, and familiarity with InfiniBand and RoCE networks.

Ways to Stand Out from the Crowd:

• Prior contributions to one or more DNN training and Inference frameworks as part of your previous work experience.
• Deep understanding and contributions to the scaling of LLMs on large-scale systems.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 24, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.