Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 4
Algorithms @ 4
CUDA @ 4
Communication @ 7
GPU @ 4
HPC
Hiring @ 4
JAX @ 7
LLVM @ 4
Performance Optimization @ 7
Profiling @ 4
PyTorch @ 7
Python @ 4
Rust @ 4
Software Development @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
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).
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
Salary and eligibility
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 July 27, 2026.
This posting is for an existing vacancy.