Job description

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. • Ability to lead projects with substantial technical and organizational ambiguity. • Excellent written and verbal communication and a record of effective cross-team collaboration. Ways to Stand Out From the Crowd: • Experience with Arm64 systems, CPU architecture, vectorization, or SVE. Experience with LTO, PGO, AutoFDO, BOLT, binary optimization, or code-layout analysis. • Hands-on experience with Clang diagnostics, AddressSanitizer, or other code-health workflows. • Familiarity with PMU analysis, perf, flamegraphs, BRBE, SPE, ETM, or similar profiling technologies. • Experience with cross-compilation, sysroots, large monorepositories, Perforce-scale development, or distributed build systems. • Experience turning a successful migration or optimization into a maintained workflow used by multiple teams. Python or other scripting experience for engineering automation and data analysis. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

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.
Use profiling, PMU data, flamegraphs, and binary/source analysis to identify actionable performance and code-quality findings.
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.
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.
Ability to lead projects with substantial technical and organizational ambiguity.
Excellent written and verbal communication and a record of effective cross-team collaboration.
Experience with Arm64 systems, CPU architecture, vectorization, or SVE. Experience with LTO, PGO, AutoFDO, BOLT, binary optimization, or code-layout analysis.
Hands-on experience with Clang diagnostics, AddressSanitizer, or other code-health workflows.
Familiarity with PMU analysis, perf, flamegraphs, BRBE, SPE, ETM, or similar profiling technologies.
Experience with cross-compilation, sysroots, large monorepositories, Perforce-scale development, or distributed build systems.
Experience turning a successful migration or optimization into a maintained workflow used by multiple teams. Python or other scripting experience for engineering automation and data analysis.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 2, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonai

Platform: eightfold
Effort: medium