Senior Computer Vision and Deep Learning Hardware Architect
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
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