Senior Software Engineer, CUDA Core Libraries

NVIDIA•Santa Clara, CA

1d•$184,000 - $356,500

About The Position

NVIDIA’s accelerated computing platform is foundational to modern HPC and AI. At the center of this platform are CUDA Core Libraries that enable developers to build fast, reliable, and scalable GPU-accelerated software. We are hiring a Senior Software Engineer to develop the Rust experience for CUDA Core Libraries. You will design safe, idiomatic Rust APIs for GPU computing while integrating closely with native C/C++ components. You will join the team building the foundational libraries, algorithms, and language/runtime infrastructure that make CUDA a speed-of-light experience for developers and AI coding agents alike.

Requirements

BS, MS, or PhD in Computer Science, Computer Engineering, or related field, or equivalent experience.
8+ years of relevant software development experience.
Strong production programming skills in Rust and C/C++, with deep understanding of Rust ownership, lifetimes, traits, generics, concurrency, and unsafe code.
Experience developing systems libraries, runtime components, and developer-facing APIs.
Practical knowledge of foreign-function interfaces and integrating Rust with C/C++ software.
Solid understanding of systems software concepts, including performance, concurrency, and API design.
Experience with parallel, heterogeneous, or GPU programming.
Experience contributing to production or open-source software, including testing, profiling, benchmarking, packaging, and code review.
Ability to work independently, define scope, and drive complex projects to completion.
Strong written communication skills and ability to work effectively in large, multi-language codebases (Rust, C/C++, build systems, toolchains, CI).

Nice To Haves

Strong understanding of CPU/GPU architecture and performance optimization, with hands-on experience in GPU-accelerated stacks (CUDA C++/Python, PyTorch, JAX, Numba, CuPy, or similar).
Proficiency with modern C++ and GPU libraries such as Thrust, CUB, and libcudacxx.
Experience with compiler infrastructure and tooling, including LLVM, Clang, or MLIR.
Experience designing safe Rust abstractions over low-level or asynchronous systems, including exposure to Python interoperability.
Demonstrated interest in developer tools, library design, and improving developer productivity

Responsibilities

Design and implement idiomatic Rust libraries and APIs for foundational CUDA functionality and GPU algorithms.
Build safe Rust abstractions over native CUDA and C/C++ interfaces.
Develop and maintain the C/C++ components required to support Rust-facing functionality.
Establish safe and efficient interoperability between Rust and C/C++, including interfaces that support downstream Python integration.
Optimize performance across Rust, native C/C++, and GPU execution boundaries.
Own features end-to-end: design, implementation, testing, profiling, benchmarking, documentation, packaging, release, and maintenance.
Improve the Rust developer experience through examples, diagnostics, build integration, compatibility testing, CI, and collaboration with C/C++, Python, compiler, and runtime engineers.
Work with users to investigate and resolve issues related to safety, correctness, usability, compatibility, and performance.