Senior Systems Software Engineer, Compute Stack Acceleration

Company: Nvidia

Location: US, CA, Santa Clara (Remote)

Salary: $184k - $287.5k per year

Type: Full-time

Remote: Yes

Posted: 2026-07-19

About this 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, laun...

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