Senior Solution Engineer, Compute Systems

The NVIDIA Experience (NVEX) Solutions Engineering team is looking for an experienced solution engineer focused on customer support of NVIDIA’s GPU accelerated platforms including DGX, HGX and MGX!

You will apply the latest AI technologies to triage customer issues, identify solutions, and keep customers delighted.

You must have excellent problem-solving abilities and communication skills and be able to contribute to multiple projects and tasks.

You will be working directly with customers to get them solutions on the latest NVIDIA platforms including the GB200 and GB300.

We are looking for an experienced engineer to triage customers' hardware platform issues and AI/ML workloads in huge datacenters of rack-scale platforms, solve customer problems, and contribute to products and software tooling.

You must have excellent problem-solving abilities, communication skills and be able to work on multiple projects and tasks.

You must be technically strong in Linux, have solid programming skills, and experience with multi-GPU platforms.

Expertise analyzing performance of distributed GPU-accelerated workloads is a plus.

AI is not optional here.

It is foundational, applied thoughtfully for all solution engineering workflows including solving customer cases and developing software, both products and internal tools.

What you'll be doing:

Provide direct support to our NVIDIA Enterprise customers to resolve or advance customer issues.

Work with engineering teams on customer issues, providing logs, reproduction, and other triage information.

Apply AI to create/update products and/or support tools.

Take ownership and drive customer issues from inception to resolution.

Document customer interactions to better enhance our knowledge base.

Apply agentic AI skills to solving customer issues and software development

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 10 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 troubleshoot, optimize, and customize Linux environments for AI/ML workloads.

Containerized solutions experience with Docker, Kubernetes, and/or 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)

developing in GPU accelerated / cloud / virtualized environments

Experience analyzing software performance of distributed workloads

Clustering or HPC data center technologies including Upper Layer Protocols (i.e., NCCL, MPI)

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.