Senior Deep Learning Communication Architect

NVIDIA is hiring a Senior Deep Learning Communication Architect in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include vLLM and PyTorch.
Level classifies it as a senior role.
Level lists 2,600+ other open roles at NVIDIA.

AI in this role

vllmpytorch

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:

The software architecture group at NVIDIA has openings for a Deep Learning Communication Architect. We scale the DNN models and training/inference frameworks to systems with hundreds of thousands of nodes.
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. 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. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and talented people in the world working for us. If you're creative and passionate about developing cloud services we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
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 November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

How we rate this

Senior Deep Learning Communication Architect at NVIDIA rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Deep Learning Communication Architect is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$288k a year.
The role is based in US, CA, Santa Clara.
The job was posted on May 20, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

vLLMPyTorch

Questions you could be asked

What's a project where you used vLLM hands-on?
Walk me through how you've used PyTorch in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: vLLM and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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