Senior Solution Engineer, Compute Systems

at Nvidia

USD 140,000-270,200 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 7 Agentic AI CUDA @ 6 Communication @ 6 Customer Support @ 4 Docker @ 4 GPU @ 4 HPC @ 4 Kubernetes @ 4 Linux @ 7 MPI @ 4 Machine Learning NCCL @ 4 Parallel Programming @ 6 Python @ 6 Slurm @ 4

Details

NVIDIA’s NVIDIA Experience (NVEX) Solutions Engineering team is seeking a solution engineer experienced in customer support for NVIDIA GPU-accelerated platforms, including DGX, HGX, and MGX. The role focuses on applying AI technologies to triage customer issues, identify solutions, support NVIDIA platforms such as GB200 and GB300, and contribute to products and software tooling.

The engineer will work directly with customers operating large datacenters and rack-scale, multi-GPU platforms. Responsibilities include troubleshooting hardware platform issues and AI/ML workloads, developing software and internal tools, and analyzing distributed GPU-accelerated workloads.

Responsibilities

Provide direct support to NVIDIA Enterprise customers to resolve or advance customer issues.
Collaborate with engineering teams by providing logs, reproductions, and other triage information.
Apply AI to create and update products and support tools.
Take ownership of customer issues from inception through resolution.
Document customer interactions to improve the knowledge base.
Apply agentic AI skills to customer issue resolution and software development.
Work occasional weekends and holidays to support customers.

Requirements

Bachelor’s degree in Computer Engineering, Electrical Engineering, or equivalent experience.
At least 5 years of engineering experience with multi-GPU platforms.
Strong system software expertise, including firmware, BIOS, kernels, drivers, and operating systems.
Strong Linux knowledge, including troubleshooting, optimization, and customization of Linux environments for AI/ML workloads.
Experience with containerized solutions such as Docker, Kubernetes, and/or Slurm.
Professional-level communication skills, including the ability to adapt communication to the audience’s technical level and remain calm and focused in negative situations.
Excellent follow-up and organizational skills, with a passion for solving problems.
Proficiency in C/C++ programming for platform operating systems, firmware, BIOS, kernels, and drivers.
Proficiency in Python and the ability to build custom tools.

Preferred Qualifications

Background in parallel programming or GPU acceleration, such as CUDA.
Experience developing in GPU-accelerated, cloud, or virtualized environments.
Experience analyzing software efficiency of distributed workloads.
Experience with clustering or HPC datacenter technologies, including upper-layer protocols such as NCCL and MPI.

Benefits

The position offers a competitive salary, equity, and benefits. The base salary range is USD 140,000–224,250 for Level 3 and USD 168,000–270,250 for Level 4. Applications will be accepted at least until September 24, 2026. NVIDIA is an equal opportunity employer.