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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - Python Numerical Computing Libraries - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $184,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Profiling, Nvidia CUDA, Computer Programming, Software Debugging, Distributed Systems, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Machine Learning, NumPy, Performance Tuning, Tensorflow, Scientific Computating, SciPy, Supercomputing, Pytorch, Deep Learning, Parallel Computation, Numerical Computing, Pandas, Information Technology, Data Analytics, Api Design - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Software-Engineer---Python-Numerical-Computing-Libraries_JR2016201 ## About the Role * BS, MS or PhD degree in Computer Science, Applied Math, Electrical Engineering or related field (or equivalent experience) * 6+ years of relevant industry experience or equivalent academic experience after BS * Excellent Python, C++ and CUDA programming skills * Strong understanding of fundamental numerical methods, dense and sparse array computing * Deep familiarity with Python numerical computing libraries (e.g. NumPy, SciPy), including accelerated implementations (e.g. CuPy, Jax.NumPy, NumS, cuNumeric) * Experience developing and publishing Python libraries, following standard methodologies for pythonic API design * Strong background with parallel programming and performance analysis Ways to stand out from the crowd: * Experience using/contributing to Python libraries for data science (e.g. Pandas), machine learning (e.g. scikit-learn) and deep learning (e.g. TensorFlow, PyTorch) * Experience with low-level GPU performance optimization * Experience building, debugging, profiling and optimizing distributed applications, on supercomputers or the cloud * Background with tasking or asynchronous runtimes * Background on compiler optimization techniques, and domain-specific language design ## Description Join our dynamic team to help develop and optimize GPU-accelerated and distributed implementations of Python numerical libraries, supporting Python-based frameworks in various ecosystems. This developer will be a crucial member of a team that is working to unlock the power of distributed GPU computing for domains such as scientific computing, data analytics, deep learning, and professional graphics, running on hardware ranging from supercomputers to the cloud! What you will be doing: * Work closely with product management and internal or external partners, to understand use cases and requirements, and contribute to the technical roadmaps of libraries * Architect, prioritize, and develop accelerated and distributed implementations of numerical algorithms * Design future-proof Python APIs for accelerated numerical/scientific computing libraries * Analyze and improve the performance of developed APIs on various CPU and GPU architectures, especially as a part of customer-critical end-to-end workflows * Prototype integrations of developed APIs into targeted frameworks * Write effective, maintainable, and well-tested code for production use * Contribute to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/1521-accelerating-python-on-gpus) - [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [CUDA Python: GPU programming for the modern developer](https://www.wearedevelopers.com/videos/100221-cuda-python-gpu-programming-for-the-modern-developer) ## Related Articles - [What’s the latest in NVIDIA CUDA Python](https://www.wearedevelopers.com/magazine/568-what-s-the-latest-in-nvidia-cuda-python) - [The 13 Best Python Libraries for Developers in 2025](https://www.wearedevelopers.com/magazine/371-the-13-best-python-libraries-for-developers-in-2025) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 good reasons why you should learn Python in 2021](https://www.wearedevelopers.com/magazine/19-7-good-reasons-why-you-should-learn-python-in-2021) - [Top 6 Hackathons for Developers in 2023](https://www.wearedevelopers.com/magazine/263-top-6-hackathons-for-developers-in-2023) - [Dev Digest 157: CUDA in Python, Gemini Code Assist and Back-dooring LLMs](https://www.wearedevelopers.com/magazine/557-dev-digest-157-cuda-in-python-gemini-code-assist-and-back-dooring-llms)