NVIDIA's accelerated computing platform is the foundation of modern HPC and AI. At the core of this platform are the CUDA Driver, CUDA Toolkit and CUDA Core Libraries-C++ and Python libraries that enable developers to write fast, reliable, scalable GPU-accelerated software and the Legate libraries that accelerate multi-GPU workflows. We are looking for an outstanding build engineer to contribute to the build, testing, packaging and developer experience to accelerate development.. This includes projects like the CUDA driver, CUDA toolkit, CCCL (Thrust, CUB, libcudacxx), cuda-python, numba-cuda, Legate and cuPyNumeric. Join the team that builds, tests and packages the foundational libraries, algorithms, language and compiler infrastructure that make CUDA a speed of light delight for developers across a wide range of workloads including deep learning, scientific computing, HPC, and data analytics. What you will be doing: • Decomposing and modularizing build processes for reusablity across multiple projects • Debugging CMake, pip, and conda issues encountered in CI and local builds • Working on scripting and infrastructure to manage dependencies across various environments and build systems • Bringing up builds and CI across platforms (x86_64/arm64) and OSes (Linux/Windows/Mac) and other unreleased hardware and software • Working with engineering leadership to identify the support matrix and manage the scope of the build matrix • Automating scheduled work for all of the above What we need to see: • Bachelor's Degree in Systems/Software/Computer Engineering, CS or equivalent experience • 8+ years of relevant industry experience or equivalent academic experience after BS • Experience working across multiple highly-coupled projects (in Git or another VCS) • Experience working with C/C++ and Python projects • Familiarity with CMake, pip, conda or other tools for C/C++ or Python build and packaging • Familiarity with CI/CD systems including Github and Gitlab • Understanding of testing principles • Knowledge of release management practices • Strong analytical, debugging, and problem-solving skills • Familiarity with containerization technologies (e.g. Docker) Ways to stand out from the crowd: • Background with or compiling for HPC/multi-node environment • Experience working with closed-source SW, confidential HW, or large code-bases (100k+ LoC) • Familiarity with binary library compilation, linking, and distribution • Exposure to development across multiple OSes • You have implemented, shipped, and EoL'd a conda package 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 June 14, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.