Senior Computer Vision and Deep Learning Hardware Architect

We're looking for an Autonomous Vehicle Performance Architecture Engineer to join the NVIDIA MMPLEX PVA team. The team designs state-of-the-art programmable vision accelerators (PVAs) for automotive and robotics applications.

You will work on delivering efficient software on PVA for Autonomous Driving solutions, analyzing and optimizing key applications for existing and new architectures, building models to predict performance, power, and reliability, and proposing new architecture features.

Responsibilities:

• Work on delivering efficient software on PVA for Autonomous Driving solutions
• Analyze, prototype, and optimize key applications for existing and new architectures for PVA
• Build models to predict performance, power, and reliability on future architectures and propose and evaluate new architecture features
• Develop tools to analyze, simulate, validate, and verify application performance and energy consumption
• Collaborate with teams to improve PVA architecture and extend the state of the art in performance, efficiency, reliability, and programmability

Requirements:

• Master's or PhD (or equivalent experience)
• 3+ years of experience in a relevant discipline (CE, CS&E, CS, AI)
• Excellent C/C++ programming and software design skills
• Strong background in computer architecture and high-performance computing
• Performance modeling, profiling, debugging, and code optimization or architectural knowledge of CPU and DSP

Preferred qualifications:

• DSP programming, performance analysis, modeling, 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