Role at a glance
- Job function
-
Software Engineering & IT Systems Software Engineering
- Salary
- Not Disclosed
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- with 8+ software engineering and HPC/AI experience
- Education
- B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience)
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Qualifications
B.S., M.S., or Ph.D. in Computer Science or a related field, or equivalent experience. Experience with deep learning frameworks or inference engines; prototyping and development using Python, C++, CUDA, or related DSLs; AI models, parallelism, or compiler technologies; AI-cluster performance benchmarking and at least one performance profiler toolchain; and HPC/AI communication concepts. Adaptability and effective collaboration across teams and time zones are also required.
Required
- Development or integration experience with deep learning frameworks such as PyTorch or JAX, and inference engines such as TRT-LLM, vLLM,...
- Rapid prototyping and development with Python, C++, CUDA, or related DSLs such as Triton or cuTe.
- A solid grasp of AI models, parallelism, and/or compiler technologies such as torch.compile.
- Experience benchmarking performance on AI clusters and familiarity with at least one performance profiler toolchain, such as PyTorch...
- Understanding of HPC/AI communication concepts, including one-sided versus two-sided communication, elasticity, resiliency, or topology...
- Adaptability and willingness to learn new areas and tools; flexibility to work and communicate effectively across teams and time zones.
Preferred
- Experience with parallel programming on at least one communication runtime: NCCL, NVSHMEM, or MPI.
- Good understanding of computer system architecture, hardware-software interactions, and operating-system principles.
- Expertise in one or more of training, distributed inference, MoE, reinforcement learning, or kernel authoring with CUDA, Triton, cuTe,...
- Experience programming for compute and communication overlap in distributed runtimes.
- Experience with AI compiler pattern matching and lowering; understanding of memory hierarchy, consistency models, and tensor layout.
About the role
Original posting provided by NVIDIA
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.
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?
What you will be doing:
Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
Improve AI compilers to hide communications or perform automatic fusion.
Conduct in-depth AI workload performance characterization on multi-GPU clusters.
Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
Influence the roadmap of communication libraries - NCCL & NVSHMEM.
Collaborate with a very dynamic team across multiple time zones.
What we need to see:
B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 8+ 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
You will also be eligible for equity and benefits.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.