System Software Engineer, Performance - CUDA Driver

Responsibilities

• Design, implement, validate, and ship performance-centric features and programming-model capabilities in the CUDA driver and runtime, writing maintainable, well-tested production C/C++.
• Optimize critical execution paths—including kernel launch, synchronization, memory management & movement, CPU–GPU coordination, and system interconnect use—for latency, throughput, bandwidth, efficiency, and scalability.
• Own complex performance problems end-to-end - understand important workloads, form hypotheses, create focused measurements and models, isolate root causes across software and hardware boundaries, implement production solutions, and validate application-level impact.
• Establish performance expectations for current and future platforms, characterize new silicon, close software and hardware gaps, and drive performance readiness through product release.
• Translate workload and platform evidence into CUDA API and programming-model improvements, systems-software direction, and measurement-backed recommendations for future hardware architecture and implementation.
• Partner with application, library, framework, operating-system, driver, runtime, firmware, GPU architecture, silicon, product, and customer-facing teams; communicate findings clearly and raise engineering quality through design and code reviews.
• Lead complex feature development and cross-layer investigations across teams, define performance requirements and technical direction for major subsystems, mentor engineers, and shape hardware/software decisions for future product generations.
• 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 2 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.

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