Senior Build Engineer - CUDA Driver, Core Libraries, Distributed Runtimes

NVIDIA • Santa Clara, CA

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About The Position

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.

Requirements

• 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)

Nice To Haves

• 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

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees