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NVIDIA

Senior Enterprise Solution Engineer

NVIDIA is hiring a Senior Enterprise Solution Engineer in Beijing, China. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include Python, Kubernetes and Docker.
  • Level classifies it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Develop enterprise software tools and container solutions to support GPU-accelerated deep learning frameworks and cloud infrastructure.

PythonKubernetesDockerAWSGoogle Cloud
systems-engineeringcontainer-orchestrationdeep-learninglinuxdistributed-systems

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.

How we rate this

Senior Enterprise Solution Engineer at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Systems EngineeringContainer OrchestrationDeep learningLinuxDistributed SystemsPythonKubernetesDocker

Questions you could be asked

  1. Tell me about a project where systems engineering was part of your work. What did you do?
  2. Tell me about a project where container orchestration was part of your work. What did you do?
  3. Tell me about a project where deep learning was part of your work. What did you do?
  4. Tell me about a project where linux was part of your work. What did you do?
  5. Tell me about a project where distributed systems was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Systems Engineering, Container Orchestration, Deep learning, Linux, and Distributed Systems. 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.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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