About this Senior Solution Engineer, Compute Systems role at NVIDIA
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)
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 (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.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
