Senior Systems Software Engineer, Compute Stack Acceleration

NVIDIA is a technology company developing solutions in artificial intelligence, high-performance computing, and visualization. The Senior Systems Software Engineer will lead cross-stack efforts to improve compute software on NVIDIA CPU platforms through toolchain, build, code-health, profiling, and optimization initiatives. The role includes validating capabilities, resolving integration blockers, automating workflows, measuring outcomes, and documenting 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