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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Deep Learning Framework Communications Engineer - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $152,000.0 - $241,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Computer Programming, Python (Programming Language), Pattern Recognition, Rapid Prototyping Process, Software Engineering, Systems Architecture, Systems Integration, Reinforcement Learning, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Parallel Computation, Information Technology - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Deep-Learning-Framework-Communications-Engineer_JR2011908 ## About the Role We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?, * B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience * Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang * Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe) * Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile) * Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems) * Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc) * Adaptability and passion to learn new areas and tools * Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: * Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) * Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes * Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Your Next AI Needs 10,000 GPUs. Now What?](https://www.wearedevelopers.com/videos/1590-your-next-ai-needs-10-000-gpus-now-what) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [The Gashlycrumb Tinies of AI Networking You Must Know (or Languish!)](https://www.wearedevelopers.com/videos/2067-the-gashlycrumb-tinies-of-ai-networking-you-must-know-or-languish) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Got AI ideas but no money? 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