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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, CUDA UMD - Graphs and GPU Sharing - **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), Computing Platforms, C++ (Programming Language), Nvidia CUDA, Computer Programming, Software Debugging, Linux, Device Drivers, Video Game Development, Scientific Computating, Software Engineering, System Software, Virtual Memory, Multithreading, Virtual Reality, Deep Learning, Parallel Computation, Information Technology, Code Testing, Codebase - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Software-Engineer--CUDA-UMD---Graphs-and-GPU-Sharing_JR2014056 ## About the Role Are you a motivated system software engineer with a deep understanding of device drivers who has phenomenal C/C++ skills? If so, this role might be for you. We are looking for a seasoned software professional to work on the CUDA Driver, a core component of our platform for accelerating general purpose computation on the GPU. You will be an integral part of a team that delivers features and improvements to better realize the potential of NVIDIA hardware for a growing range of computational workloads, ranging from deep learning, scientific computation, data science and self-driving cars to video games and virtual reality., * BS or MS degree in Computer Science, Electrical Engineering or related field (or equivalent experience) * Strong C and C++ programming skills * Minimum of 8-10 years of related development experience * Experience driving projects across multiple teams * Experience working with large codebases * Background with operating system interfaces for threads, process control, and virtual memory * Experience writing and debugging multithreaded programs * Good written communication as well as presentation skills Ways to stand out from the crowd: * Prior experience with parallel computing - preferably writing CUDA Programs or Libraries that use CUDA * Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO * Knowledge of memory coherence and consistency models * Background with kernel mode development * Experience with Linux Systems Software development ## Description As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best compute platform in the world. You will craft elegant solutions to exciting problems and shape the future direction of CUDA as you collaborate with your peers across NVIDIA. * Evangelize, architect, and implement new features * Coordinate and drive development efforts across multiple teams * Help define forward-looking improvements to the CUDA APIs and programming model * Extend important CUDA programming models and functionality such as CUDA Graphs and MPS (Multi-Process Service) * Write effective, maintainable, and well-tested code * Develop code for multiple operating systems ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [The weekly developer show: Boosting Python with CUDA, CSS Updates & Navigating New Tech Stacks](https://www.wearedevelopers.com/videos/1293-the-weekly-developer-show-boosting-python-with-cuda-css-updates-navigating-new-tech-stacks) - [CUDA Python: GPU programming for the modern developer](https://www.wearedevelopers.com/videos/100221-cuda-python-gpu-programming-for-the-modern-developer) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) ## Related Articles - [What’s the latest in NVIDIA CUDA Python](https://www.wearedevelopers.com/magazine/568-what-s-the-latest-in-nvidia-cuda-python) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers) - [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) - [Top 6 Hackathons for Developers in 2023](https://www.wearedevelopers.com/magazine/263-top-6-hackathons-for-developers-in-2023)