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