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What you'll be doing:
Provide direct support to our NVIDIA Enterprise customers and work to answer questions, reproduce, resolve, or advance customer issues.
Work with engineering teams on customer issues, providing logs, reproduction information, and other triage information.
Create/update product and/or support tools.
Take ownership and drive customer issues from inception to resolution.
Document customer interactions and better enhance our knowledge base.
Develop features and tools as part of solution engineering efforts to support NVIDIA technologies
Occasional work on weekends and holidays to support customers
What we need to see:
Minimum of a BS in Computer Engineering, Electrical Engineering, or equivalent experience.
At least 5+ years of engineering experience with multi-GPU platforms
Strong system software (firmware, BIOS, kernel, driver, operating system) expertise
Solid understanding of Linux and the ability to analyze, optimize, and customize Linux environments for AI/ML workloads.
Containerized solutions experience with Docker, Kubernetes, Slurm
Professional-level communication skills, including adjusting communication to the technical level of the audience, and staying calm and focused in negative situations.
Excellent follow-up and organizational skills, with a passion or love for solving problems.
Proficient in C/C++ programming of platform OS, firmware, BIOS, kernel, drivers
Proficient in Python programming with the ability to build custom tools
Ways to stand out from the crowd:
Background with parallel programming or GPU acceleration (e.g., CUDA)
Experience developing in GPU accelerated / cloud / virtualized environments
Experience analyzing software performance of distributed workloads
Clustering or HPC data center technologies including Upper Layer Protocols (NCCL, MPI)
You will also be eligible for equity and .
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