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Senior Enterprise Solution Engineer

NVIDIA Corporation

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Skills named in this posting

  • Python
  • Virtualization
We are looking for an experienced system engineer, who will play a dual role on the NVIDIA Enterprise Experience (NVEX) team. An awesome candidate is highly technical who can triage customer software issues and resolve customer problems as well as someone who can develop key enhancements and tools for the DGX Platform Software, Container Orchestrators, Deep Learning containers, and potentially other Enterprise related system software. This individual should have proven grasp of platform and systems engineering who understands Linux internals, knowledge about servers and has the ability to resolve hardware and/or OS internal issues. If you have a real passion for technology, and you are interested in a role that you can make a difference in and contribute at all different levels, this may be a phenomenal position for you. What you'll be doing: • Develop features and tools as part of solution engineering efforts to support all Enterprise Service offerings including, but not limited to DGX, NVAIE, Container Orchestrators (such as Kubernetes), GPU accelerated applications, and Deep Learning frameworks. • Work with NVIDIA Enterprise customers and internal users to improve the availability, reliability, and overall experience of working with NVIDIA Deep Learning Framework containers on NVIDIA GPUs. • Take ownership and drive customer issues on containers, Deep Learning frameworks, and Cloud deployment from inception to resolution. • Build upon the opportunity to research new use cases with GPUs for emerging container technologies and Deep Learning frameworks. • Bring independent analysis, communication, and problem-solving to customer experience. • Be on call one weekend per month in the event a customer has a Sev1 outage and requires engineering assistance. What we need to see: • BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience). • At least 5 years system software development and troubleshooting experience, ideally with some customer facing. • Intellectual curiosity, positive attitude, flexibility, analytical ability, self-motivation, and team-oriented. • Strong computer science concepts and excellent knowledge of Python and scripting methodologies. • Deep understanding of at least two of the following: data centers, servers, distributed systems, virtualization, deep learning frameworks, containers/containerization (ie Docker, Kubernetes), hybrid cloud (ie AWS, GCP). • You'd have cultivated a deep Linux knowledge, and be very comfortable working in various Linux environments as well as with Windows OS’s. • Professional-level communication skills, interpersonal skills with a passion to solve problems. Ways to stand out from the crowd: • Proven experience in developing, triaging and debugging on Linux and Containers and deep learning frameworks. • Experience working with distributed systems especially container orchestrators. • Any exposure to system level debug and triaging experience. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are expanding fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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