Hardware Architect, Deep Learning GPU and System

Job description

At NVIDIA, we push the boundaries of Artificial Intelligence using Deep Learning every day, designing better algorithms, hardware and software. By joining the Compute Deep Learning Architecture team you would be in an outstanding position to influence all three and help us push the boundaries even farther in large number of fields like datacenters and autonomous machines. We are looking for remarkable candidate passionate about AI and Deep Learning as much as we are. Would you like to make a difference? What you'll be doing: As a member of our Hardware architecture deep learning team, you will contribute to features that help next-generation GPUs and systems advance the state of AI. This position requires you to collaborate with other hardware and software engineers as well as DL researchers. Your day to day work will include analyzing the behavior of various deep learning methods on current and future hardware architectures and propose new features to accelerate it. The features could be HW, SW or Algorithmic - usually combining all. The main focus of this job is from hardware architecture perspective and workload performance. What we need to see: A degree or equivalent experience in computer science, electrical engineering or related field. 2+ years of experienc e in at least some of the following relevant areas is required: Performance, Hardware Architecture, Deep Learning analysis. A familiarity with GPU computing (Nvidia or others) is a plus. Excellent interpersonal skills, people who like to collaborate and work within a team. innovation, motivation and passion. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. An AI-powered robot can communicate and learn motor skills through trial and error. This is truly an outstanding time. The era of AI has begun. Come and join us!