Senior Computer Vision and Deep Learning Hardware Architect

Job description

We’re looking for an Autonomous Vehicle Performance Architecture Engineer. NVIDIA MMPLEX PVA team is designing the state-of-art programmable vision accelerator (PVA) which targets the automotive and robotic area. We are responsible for the architecture modeling, designing and verifying. We also deliver most high-performance/efficient computer vision applications and kernels to the world-wide customers. What you'll be doing: Work on delivering most efficient software on PVA for Autonomous Driving solutions Analyze, prototype and optimize key applications for both existing and new architectures for PVA Build model to predict performance, power and reliability on future architectures and propose and evaluate new architecture features Be involved in crafting tools to analyze, simulate, validate and verify application performance and energy consumption Collaborate with different teams to improve the PVA architecture to extend the state of the art in performance, efficiency, reliability and programmability What we need to see: Master's or PhD (or equivalent experience) 3+ years of experience equivalent experience in relevant discipline (CE, CS&E, CS, AI) Excellent C/C++ programming and software design skills Strong background in computer architecture, high performance computing Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and DSP Ways to stand out from the crowd: DSP programming, performance analysis, modelling and optimization experience (GPU programming experience is a plus) Autonomous vehicle software development experience Expertise in characterizing and modeling system-level performance, executing comparison studies, and documenting and publishing results Experience in deep learning, computer vision and self-driving car domain