Optimize critical CUDA primitives, memory management and movement, CPU–GPU coordination, and interconnect paths for latency, throughput, bandwidth, efficiency, and scalability.
Establish performance goals for current and future platforms, characterize as new platforms come online, close software and hardware gaps, and drive performance readiness through releases.
Translate workload and platform evidence into CUDA API, programming model, system software, and future GPU architecture recommendations.
Set subsystem performance direction and mentor engineers tackling complex systems and performance challenges.
Influence technical decisions with clear performance evidence and tradeoffs and strengthen implementations through rigorous design and code reviews.
What we need to see
A BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field—or equivalent practical experience — with at least 7+ years of relevant systems-software development experience.
Strong production C/C++ systems-programming experience, including delivery of substantial features, optimizations, or production fixes in a complex codebase.
Strong operating systems and concurrency foundations, including threads, synchronization, processes, virtual memory, and user/kernel interactions.
Strong computer architecture foundations, including processors, memory hierarchy, caching and coherence, data movement, and system interconnects.
Demonstrated success improving real software performance: measuring behavior, identifying bottlenecks, implementing optimizations, and profiling to prove their effectiveness.
Sound technical judgment, ownership of ambiguous problems, and clear communication across organizational and disciplinary boundaries.
Direct CUDA or GPU experience is valuable but is not required when accompanied by deep systems software, operating systems, computer architecture, and performance-engineering foundations.
Ways to stand out from the crowd
Experience developing GPU or accelerator drivers, runtimes, kernel software, firmware, compilers, or other performance-critical low-level systems.
Experience with pre-silicon analysis, platform bring-up, performance modeling, or hardware/software co-design.
Systems-level performance experience with AI/DL, HPC, graphics, automotive, robotics, or similarly demanding workloads.
Evidence of technical inventions such as software-performance patents, novel production designs, or measurement-backed recommendations that influenced hardware revision or future architecture.
Python or another scripting language used for focused experimentation, data analysis, or visualization.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 October 18, 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.
