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What you'll be doing:
Our day-to-day work involves guiding partners in their adoption of end-to-end Machine Learning and Deep Learning solutions, using NVIDIA's compute, networking, and software stacks. Don't think this is a high-level slideshow job - we are the voice of experience, using Kubernetes, SaaS,infrastructure-as-codetools, network debugging, and problem solving skills to help build modern AI factories.
We also excel at sharing knowledge with others, whether it's delivering demos, assisting with proof-of-concepts, or writing papers and developer blogs. By collaborating with executives and engineering, we solve complex problems and help bring NVIDIA's premiere technologies to life in the cloud and in the datacenter.
Our mission is to solve the problems that nobody else has solved yet, and we need someone to be an instrumental part of that!
What we need to see:
Strong foundational expertise and a BS, MS, or PhD in Engineering, Computer Science, or a related field or equivalent experience.
Established track record working with AI and HPC clusters, both on-premises and cloud based.
12+ years of proven experience with cluster management and related tools, including Docker Containers, Slurm, Kubernetes, and Ansible.
Hands-on experience with network, storage, cluster configuration and debugging.
Strong analytical and problem-solving skills, along with an ability to articulate what you know to others.
Ability to multitask efficiently in a dynamic environment.
Ways to stand out from the crowd:
Strong coding and debugging skills, including experience with Python, C/C++, Bash, and Linux utilities.
Demonstrated expertise through projects or Open Source contributions involving GPU workloads, Kubernetes, InfiniBand, Ethernet, or other areas related to high-performance clusters and hybrid cloud solutions.
Exhibit hands on experience with NVIDIA AI Enterprise, Base Command Manager and NEMO cloud native framework.
Willingness and ability to learn quickly and solve advanced problems.
You will also be eligible for equity and .
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