GPU Systems Infrastructure Engineer
Location: Fremont, CA
Our client develops and supports sophisticated technology infrastructure built to handle complex, performance-intensive applications. They are seeking a hands-on engineer who can bring together NVIDIA GPU technology, compute platforms, storage, networking, and clustered infrastructure into high-performing solutions. This role offers the opportunity to work across the full systems lifecycle, solve challenging technical problems, and make a meaningful impact in an environment where initiative, technical curiosity, and personal ownership are highly valued.
This Role Offers
- Work with diverse technologies and solutions that span multiple areas of sophisticated technical infrastructure.
- Exposure to a diverse range of advanced systems, platforms, and supporting infrastructure technologies.
- A team-oriented culture that encourages proactive problem-solving, personal ownership, clear communication, and dependable execution.
Focus
- Own the technical lifecycle of NVIDIA GPU compute environments, from architecture and component selection through validation, rollout, and ongoing support.
- Build and refine GPU-accelerated platforms for demanding AI, machine learning, and high-performance computing workloads.
- Integrate compute servers, engineering workstations, storage, and network components into reliable end-to-end infrastructure.
- Validate new configurations through benchmarking, stress testing, performance analysis, and structured troubleshooting.
- Identify and resolve technical challenges across various system environments while ensuring issues are addressed through completion.
- Partner with customer-facing and commercial teams to translate workload needs into practical, supportable technical solutions.
- Evaluate evolving GPU, server, storage, networking, and cluster technologies to inform future platform decisions.
- Demonstrate initiative and accountability while working independently and maintaining strong communication and teamwork.
Skill Set
- Hands-on experience working with a range of modern systems and technical solutions.
- Demonstrated experience designing, validating, deploying, and supporting GPU-accelerated infrastructure.
- Strong server and compute systems foundation, including an understanding of how GPUs integrate with the surrounding platform and infrastructure.
- Experience working across technologies such as servers, technical workstations, storage platforms, networking, and multi-node compute environments.
- Proven ability to identify and resolve complex technical challenges across a variety of systems and environments.
- Exposure to benchmarking, performance tuning, system validation, or workload optimization in accelerated computing environments.
- Strong problem-solving skills with the ability to move from technical investigation to practical resolution.
- High level of commitment, ownership, self-direction, collaboration, and communication.
- Several years of relevant experience in GPU computing, HPC, AI platforms, or large-scale infrastructure is preferred, but demonstrated technical capability and depth of experience will carry greater weight than a specific tenure threshold.
- Bachelor’s degree in computer science, Engineering, or a related technical discipline is preferred, or equivalent relevant experience.
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