Senior Computer Vision and Deep Learning Hardware Architect

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