Senior Systems Software Engineer, Compute Stack Acceleration

About the role

NVIDIA is growing a senior engineering team focused on making our compute software stack first-class on NVIDIA CPU platforms. The team turns modern toolchains, build and code-health practices, performance-analysis workflows, and optimization techniques into repeatable improvements across real software components.

We are looking for an experienced systems software engineer who can lead cross-stack engineering efforts from an ambiguous adoption problem to a measurable outcome. You will work closely with compiler, platform, performance, library, and application teams to validate new capabilities, resolve integration blockers, produce credible before-and-after evidence, and turn successful approaches into reusable engineering practices. Depending on your background and project needs, your initial work may emphasize toolchain, build, and code-health adoption or profiling, optimization, and evidence-routing workflows. The role is intentionally broad enough to evolve as the team identifies the highest-leverage opportunities across the stack.

What You'll Be Doing:

- Lead toolchain, build, code-health, and performance-workflow adoption projects across large software components.

- Evaluate and deploy supported GCC and LLVM/Clang toolchains, compiler options, linkers, sysroots, and cross-compilation configurations.

- Integrate modern toolchains and workflows into complex build systems and continuous-integration environments.

- Establish useful Clang diagnostic builds and targeted sanitizer coverage in partnership with component owners. Evaluate techniques such as link-time optimization, profile-guided optimization, AutoFDO, and BOLT on representative software.

- Use profiling, PMU data, flamegraphs, and binary/source analysis to identify actionable performance and code-quality findings.

- Build automation, wrappers, validation scripts, dashboards, and migration helpers where they improve adoption and repeatability. Measure changes in runtime, code size, build time, launch latency, throughput, quality, or engineering velocity.

- Drive complex blockers to the appropriate compiler, runtime, library, infrastructure, or component owner.

- Document validated approaches as reusable playbooks for other engineering teams. Communicate technical results and tradeoffs clearly to engineers and leadership.

What We Need to See:

- BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience. 8+ years of relevant systems software engineering experience.

- Strong C and C++ development, debugging, and code-review skills.

- Strong Linux systems knowledge and hands-on experience with complex native software stacks.

- Practical experience with GCC or LLVM/Clang, linkers, compiler options, and build systems.

- Experience working in large, multi-component codebases and CI environments.

- Experience with performance profiling, root-cause analysis, and before-and-after validation.