Senior Software Engineer, CUDA Core Libraries

NVIDIA

Senior Software Engineer developing CUDA Core Libraries for GPU computing at NVIDIA. Involving C++ and Python libraries, optimizing algorithms, and ensuring high performance in AI and HPC.

Posted 6/1/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Develop and implement CUDA Core Libraries in C++ and/or Python, including parallel algorithms and idiomatic language bindings for core CUDA functionality
Compose, optimize, and evolve GPU algorithms and APIs, from high-level interfaces down to low-level performance tuning involving memory, parallelism, and synchronization
Own features end-to-end: develop, implementation, testing, benchmarking, documentation, and long-term maintenance
Improve developer experience across the stack: CI, tests, benchmarks, packaging, examples, and docs
Collaborate with senior CUDA engineers in design reviews, code reviews, and open-source-style workflows
Engage with real users through issues, performance investigations, and API feedback

Requirements

What you’ll need

BS, MS, or PhD in Computer Science, Computer Engineering, or a related field or equivalent experience
Minimum of 8+ years of related development experience
Strong programming skills in C++, Python, or both, with proven interest in systems-level software (performance, memory, concurrency, API design)
Solid understanding of modern C++ (templates, generics, standard library) and/or Python library development and packaging
Practical experience with parallel or heterogeneous programming (CUDA, OpenMP, GPU-accelerated Python, or similar)
Experience contributing to production software or open-source libraries, including testing, profiling, and code review
Ability to work independently, scope problems, and drive projects to completion
Clear written communication for technical design and documentation
Comfort navigating large, multi-language codebases (C++, Python, CMake, Pixi, CI systems)

Benefits

Comp & perks

equity
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Hard Skills & Tools

C++PythonCUDAOpenMPGPU programmingparallel algorithmsAPI designperformance tuningmemory managementconcurrency

Soft Skills

independent workproblem scopingproject managementclear written communicationcollaborationcode reviewdesign review