Senior Software Engineer, CUDA Rust Core Libraries

NVIDIA develops accelerated computing platforms foundational to high-performance computing and artificial intelligence. The company is seeking a Senior Software Engineer to develop idiomatic, safe Rust libraries and APIs for CUDA Core Libraries, integrate them with native C/C++ components, optimize GPU performance, and improve the developer experience through testing, tooling, documentation, and user support.

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

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)
• 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