Senior Systems Software Engineer, Compute Stack Acceleration

NVIDIA is hiring a senior systems software engineer to improve adoption of toolchains, build and code-health practices, and performance workflows across its compute software stack. The role partners with compiler, platform, performance, library, and application teams to resolve integration blockers, validate measurable outcomes, and establish reusable engineering practices.

Responsibilities:

• 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

Requirements:

• 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