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 the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication runtimes like NCCL and NVSHMEM for Deep Learning and HPC applications. We are looking for a motivated Partner Enablement Engineer to guide our key partners and customers with NCCL. Most DL/HPC applications run on large clusters with high-speed networking (Infiniband, RoCE, Ethernet). This is an outstanding opportunity to get an end to end understanding of the AI networking stack. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
Engage with our partners and customers to root cause functional and performance issues reported with NCCL
Conduct performance characterization and analysis of NCCL and DL applications on groundbreaking GPU clusters
Develop tools and automation to isolate issues on new systems and platforms, including cloud platforms (Azure, AWS, GCP, etc.)
Guide our customers and support teams on HPC knowledge and standard methodologies for running applications on multi-node clusters
Document and conduct trainings/webinars for NCCL
Engage with internal teams in different time zones on networking, GPUs, storage, infrastructure and support.
What we need to see:
B.S./M.S. degree in CS/CE or equivalent experience with 5+ years of relevant experience. Experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)
Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
Experience working with engineering or academic research community supporting HPC or AI
Practical experience with high performance networking: Infiniband/RoCE/Ethernet networks, RDMA, topologies, congestion control
Expert in Linux fundamentals and a scripting language, preferably Python
Familiar with containers, cloud provisioning and scheduling tools (Docker, Docker Swarm, Kubernetes, SLURM, Ansible)
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 conducting performance benchmarking and developing infrastructure on HPC clusters. Prior system administration experience, esp for large clusters. Experience debugging network configuration issues in large scale deployments
Familiarity with CUDA programming and/or GPUs. Good understanding of Machine Learning concepts and experience with Deep Learning Frameworks such PyTorch, TensorFlow
Deep understanding of technology and passionate about what you do
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 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.Skills Required
- B.S./M.S. degree in CS/CE or equivalent experience
- 5+ years of relevant experience in HPC or AI
- Excellent C/C++ programming skills
- Experience with parallel programming and communication runtimes
- Practical experience with high performance networking technologies
- Expertise in Linux and scripting languages, preferably Python
- Familiarity with cloud provisioning and scheduling tools
- Experience in performance benchmarking on HPC clusters
- Familiarity with CUDA programming and/or GPUs
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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