Role at a glance
- Salary
- Not Disclosed
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years of relevant software development experience.
- Education
- BS, MS, or PhD in Computer Science, Computer Engineering, or related field, or equivalent experience.
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Role Summary
Develops the Rust experience for CUDA Core Libraries, creating Rust APIs and abstractions for GPU computing and integrating them with native C/C++ components. The role also improves the developer experience and performance across Rust, C/C++, and GPU execution.
What You'll Do
- Design and implement idiomatic Rust libraries and APIs for CUDA functionality and GPU algorithms.
- Build safe Rust abstractions over native CUDA and C/C++ interfaces, and develop supporting C/C++ components.
- Establish Rust and C/C++ interoperability, including interfaces that support downstream Python integration.
- Optimize performance across Rust, native C/C++, and GPU execution boundaries.
- Own features through design, implementation, testing, profiling, benchmarking, documentation, packaging, release, and maintenance.
- Improve examples, diagnostics, build integration, compatibility testing, and CI; work with users to investigate and resolve safety,...
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View full postingQualifications
Requires a BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience, and 8+ years of relevant software development experience. Requires production Rust and C/C++ programming skills, including deep knowledge of Rust ownership, lifetimes, traits, generics, concurrency, and unsafe code; experience with systems libraries, runtime components, developer-facing APIs, foreign-function interfaces, Rust/C/C++ integration, and parallel, heterogeneous, or GPU programming; and experience contributing to production or open-source software, including testing, profiling, benchmarking, packaging, and code review. Also requires systems-software knowledge, independent project ownership, strong written communication, and ability to work in large multi-language codebases.
Required
- Strong production programming skills in Rust and C/C++, with deep understanding of Rust ownership, lifetimes, traits, generics,...
- 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,...
Preferred
- Strong understanding of CPU/GPU architecture and performance optimization, with hands-on experience in GPU-accelerated stacks (CUDA...
- 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
What you’ll be doing:
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.
What we need to see:
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).
Ways to stand out from the crowd:
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
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.