Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!
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:
Experience working 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
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
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 March 29, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
