Software Engineer, Performance Instrumentation

About the role

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA is looking for a Software Engineer, Performance Instrumentation to join our outstanding team in Santa Clara, CA. This is an outstanding opportunity to be part of a world-class organization, driving innovation at the intersection of AI and accelerated computing. As a part of our team, you will work on groundbreaking projects and have a direct impact on the future of technology.

What you’ll be doing:

- Define and maintain the performance data requirements from various sources including profiling libraries, annotation APIs, frameworks, runtimes, communication libraries, schedulers, configurations, and infrastructure telemetry.

- Identify and prove visibility gaps with concrete evidence, demonstrating which diagnoses are not possible with current data. Collaborate with relevant teams to address these gaps or build solutions where necessary.

- Inform the build of low-overhead instrumentation and annotation APIs from the perspective of the consumer, ensuring the necessary information is conveyed efficiently and effectively.

- Ensure data quality at ingestion by implementing validation, sanitization, checks, and alerting mechanisms, so that any gaps or errors are detected before impacting users or automated analysis.

- Measure and manage the overhead and observer effects of instrumentation on real workloads, ensuring they remain within acceptable limits.

- Collaborate with multiple partner teams simultaneously, managing commitments and ensuring continuous progress.

What we need to see:

- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.

- 8+ years of relevant software engineering experience, including hands-on experience with instrumentation or tracing in production machine learning or systems software.

- Proficiency in CUDA, and working knowledge of machine learning frameworks like PyTorch or JAX, as well as annotation or tracing APIs such as NVTX.

- Demonstrated experience in maintaining data quality in a pipeline, including validation, checks, alerting, and provenance.

- Proven ability to measure instrumentation overhead and make trade-offs among overhead, fidelity, sampling, and aggregation.

- Proven history of implementing modifications in code managed by other groups by identifying requirements, reaching consensus on interfaces, and ensuring completion through to delivery.