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It’s a unique legacy of innovation that’s fueled by great technology-and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.\nWe are looking for outstanding software engineers to join the NVIDIA Run:ai core team. The team is responsible for building the next generation of GPU sharing and checkpoint-restore technologies within CUDA and the open-source ecosystem. In this role, you will design sophisticated low-level architectures and collaborate with global engineering teams across the entire GPU software stack, contributing to the CUDA ecosystem that powers AI and ML workloads across the world.\nWhat you'll be doing:\nWork and design enhancements for CUDA libraries and system drivers\nContribute to open-source frameworks, engaging with the community and users\nBuild a complex multi-threaded modular architecture of low-level components that interact with the OS and each other in distributed environments\nEffectively write efficient, maintainable, and well-tested code for Linux powered systems.\nDevelop a solution that can run on bare-metal, on-prem, and cloud environments (Docker containers, Kubernetes)\nWork with other worldwide teams (software, hardware, architecture)\nWhat we need to see:\nB.Sc, M.Sc or equivalent experience in Computer Science, Engineering, or a related field\n5+ years of “hands on” experience developing or maintaining user space libraries and frameworks, especially for the Linux OS\nProved programming skills in C, C++, or Rust\nGood knowledge of operating systems concepts and primitives\nStrong English written and oral communication skills to collaborate with other specialists or teams globally (worldwide).\nWays to stand out from the crowd:\nCollaborative team member with strong communication skills\nEnd-to-end execution of robust technical solutions from design to production\nKnowledge and understanding of virtualization and containerization technologies for cloud and on-prem environments\nFamiliarity with kernel and driver development\nHands on experience in one of: accelerated compute, CUDA development, HPC, Deep Learning & Machine Learning frameworks such as PyTorch\nWidely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. 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