Evaluate and improve compute and GPU selection, scheduling and placement, concurrency, worker and runner configuration, resource sharing, caching, and input/output paths.
Make retry causes, recovery outcomes, and wasted execution capacity visible. Work with component owners to eliminate recurring failures and unnecessary re-execution.
Implement and validate infrastructure-level changes with application, build and CI, remote-execution, and infrastructure teams. Measure the effect on turnaround, successful efficiency, stability, usable capacity, and cost.
Turn successful investigations into supported workflows, diagnostics, documentation, and clear customer handoffs.
What we need to see
Over 8 years of solid software engineering experience working with production compute infrastructure, distributed systems, large-scale build and test systems, or comparable systems software.
Hands-on experience debugging complex performance or reliability issues across software and hardware boundaries using logs, metrics, traces, profiling, and experiments.
Proficiency in a systems programming or automation language and experience delivering tested changes into production infrastructure.
In-depth experience with Linux and proficiency in one or more of these fields: GPU systems and drivers, scheduling and resource management, remote execution or CI infrastructure, storage and data paths, or host and container infrastructure.
Ability to work across teams with different component ownership, turn ambiguous symptoms into a clear technical plan, and explain results to engineering customers.
A degree in computer science, computer engineering, or a related field, or equivalent experience.
Ways to stand out from the crowd
Experience with GPU sharing and isolation, CUDA execution behavior, MIG or MPS or equivalent experience, GPU driver diagnostics, or high-performance computing workloads.
Experience with workload placement, CPU and GPU concurrency, NUMA, cloud-instance benchmarking, or cost and performance tradeoffs.
Familiarity with Bazel, remote execution, build front ends, simulation or replay workloads, and hardware-in-the-loop validation.
Experience improving file-system, caching, networking, or high-throughput data paths under concurrent workloads.
A record of building customer self-service or observability tools and using incident and retry data to drive verified reliability improvements.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
#LI-Hybrid
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
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.
