Senior Deep Learning Performance Architect

Job Description

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company. What you will be doing: * As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning. * Prototype key deep learning and data analytics algorithms and applications. * Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites. * Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping. * Collaborate across the company to guide the direction of machine learning, working with software, research and product teams. What we need to see: * Master’s or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience. * 4+ years of relevant work or research experience. * A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture. * A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks. * Fluency in programming languages such as Python, C, C++. * Experience and familiarity with GPU computing and parallel programming models. * You have firsthand work experience with analytical performance modeling, profiling, and analysis. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA’s GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of comp…