CUDA Systems Engineer — High-Performance Driver & Runtime

NVIDIA; United States; On-site; USD 130,000 - 170,000; Full time

Job summary

NVIDIA is seeking systems software engineers to design and ship production C/C++ features in the CUDA driver and runtime, tracing workloads from application to GPU. You will optimize critical paths, bring up new platforms, and translate evidence into future software directions, collaborating across teams to improve performance and scalability.

Ideal candidates have strong OS/concurrency foundations, solid computer-architecture knowledge, and a track record of delivering production performance

Qualifications

• BS/MS/PhD or equivalent practical experience in CS/CE/EE with 2+ years in systems software.
• Strong production C/C++ systems programming and production features.
• Solid OS and concurrency fundamentals; hardware and memory systems awareness.

Responsibilities

• Design, implement, validate, and ship performance-centric CUDA driver/runtime features in production C/C++.
• Trace workloads across application, OS, CPU, interconnect, and GPU boundaries.
• Bring up new platforms and turn evidence into software and hardware direction.
• Own complex performance problems end-to-end across software/hardware boundaries.
• Set performance expectations and drive readiness for future silicon and platforms.
• Translate workload evidence into CUDA API and programming-model improvements.
• Collaborate with cross-functional teams; communicate findings and improve engineering quality.

Skills

Production C/C++ systems-programming

Operating systems & concurrency

Computer architecture foundations

Performance optimization

Communication & collaboration

CUDA/GPU experience (beneficial)

Ownership of complex problems

Education

BS/MS/PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent

Tools

CUDA

Job description

NVIDIA is seeking systems software engineers to design and ship production C/C++ features in the CUDA driver and runtime, tracing workloads from application to GPU. You will optimize critical paths, bring up new platforms, and translate evidence into future software directions, collaborating across teams to improve performance and scalability.

Ideal candidates have strong OS/concurrency foundations, solid computer-architecture knowledge, and a track record of delivering production performance