Senior Software Engineer, CUDA Core Libraries
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Job Description
Senior Software Engineer developing CUDA Core Libraries for NVIDIA's HPC and AI platform. Implementing C++ and Python solutions with a focus on performance and usability.
Responsibilities:
- 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:
- 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:
- equity
- benefits
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