Senior Software Engineer - CUDA and Unified Memory

Reposted Yesterday
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Hiring Remotely in Australia
Remote
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves designing and implementing new features for the CUDA driver, collaborating with teams, and developing code for Linux operating systems, specializing in GPU computation and memory management.
Summary Generated by Built In

We are hiring software engineers to work on the CUDA driver, a core component of our platform for accelerating general purpose computation on the GPU. Our team 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, and self-driving cars to video games and virtual reality!  

CUDA defines a unified programming model across a range of system configurations and hardware capabilities. To accomplish this, the CUDA driver interacts with GPU hardware, kernel mode drivers, and the operating system. Unified Memory kernel driver provides kernel memory management that enables these advanced features.  

What you'll be doing:  

As a member of our team, you will apply your design, coding expertise, and creativity, and to collaborate with peers across NVIDIA to deliver upon the best compute platform in the world. You will craft sophisticated solutions to exciting problems shaping the future direction of CUDA!  

  • Architect, and implement new features for new chips and new kernel features  

  • Coordinate with other teams to accomplish your work daily  

  • Help define forward-looking improvements to the CUDA APIs and programming model  

  • Write effective, maintainable, and well-tested kernel and userspace code  

  • Develop code for multiple Linux operating systems  

What we need to see:  

  • BS or MS degree in Computer Science, Electrical Engineering or related field (or equivalent experience)  

  • Strong C programming skills

  • Minimum of 8+ years of related development experience  

  • 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

Ways to stand out from the crowd:  

  • Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO 

  • Knowledge of memory coherence and consistency models  

  • Experience with kernel mode development  

  • Experience with Windows, Linux, or macOS driver development  

  • Some familiarity w C++​

Top Skills

C
Cuda
Kernel Mode Development
Linux
Operating System Interfaces
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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