Senior Systems Software Engineer

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. 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.

We 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.

What You'll Be Doing

• Work and design enhancements for CUDA libraries and system drivers
• Contribute to open-source frameworks, engaging with the community and users
• Build a complex multi-threaded modular architecture of low-level components that interact with the OS and each other in distributed environments
• Effectively write efficient, maintainable, and well-tested code for Linux powered systems.
• Develop a solution that can run on bare-metal, on-prem, and cloud environments (Docker containers, Kubernetes)
• Work with other worldwide teams (software, hardware, architecture)
  
  

• B.Sc, M.Sc or equivalent experience in Computer Science, Engineering, or a related field
• 5+ years of “hands on” experience developing or maintaining user space libraries and frameworks, especially for the Linux OS
• Proved programming skills in C, C++, or Rust
• Good knowledge of operating systems concepts and primitives
• Strong English written and oral communication skills to collaborate with other specialists or teams globally (worldwide).
  
  

• Collaborative team member with strong communication skills
• End-to-end execution of robust technical solutions from design to production
• Knowledge and understanding of virtualization and containerization technologies for cloud and on-prem environments
• Familiarity with kernel and driver development
• Hands on experience in one of: accelerated compute, CUDA development, HPC, Deep Learning & Machine Learning frameworks such as PyTorch