Senior Deep Learning Hardware Architect

At NVIDIA, we push the boundaries of Artificial Intelligence using Deep Learning every day, by designing better algorithms, hardware and software. By joining the Compute Deep Learning Architecture team you would be an outstanding position to influence all three and help us push the boundaries even farther in large number of fields like autonomous machines and datacenters. We are looking for remarkable candidate passionate about AI and Deep Learning as much as we are. Would like to make a difference?

What You'll Be Doing

• As a member of our deep learning architecture team, you will contribute to features that help next-generation GPUs advance the state of AI.
• This position requires you to keep up with the latest DL research and collaborate with DL researchers, hardware architects, and software engineers.
• Your day to day work will include analyzing the behavior of various deep learning methods on current and future architectures, proposing new features to accelerate, improve efficiency or enable various methods, and studying the benefits of the proposed features. The features could be at an Algorithmic, SW or Hardware level - many times combining all three.
  
  

• A degree in computer science, computer architecture, electrical engineering or related field or equivalent experience.
• 12+ years of meaningful experience in at least a few of the following relevant areas is required in your work history: Machine learning (with focus on Deep Neural Networks), including a solid understanding of DL fundamentals; Consistent track record architecting hardware solutions for Machine Learning; large experience in computer or chip architecture.
• A familiarity with GPU computing (CUDA, OpenCL, OpenACC) is a huge plus.
• We are looking for candidates with excellent interpersonal skills, and an aptitude for collaboration and teamwork.