Senior Software Performance Engineer - AV Platform

NVIDIA•Us, CA

About The Position

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error — this is truly an extraordinary time and the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Make the choice to join us today. We are now looking for a Senior Software Performance Engineer for Autonomous Vehicles! Our team builds NVIDIA’s end-to-end autonomous driving applications. We are seeking senior software engineers who are passionate about performance with interest in optimizing self-driving solutions that run on NVIDIA’s multi-computer and heterogenous HW architectures.

Requirements

MS or PhD degree in Computer Science, Computer Architecture, Electrical Engineering or related field (or equivalent experience).
10+ years of relevant professional experience working on autonomous vehicles software.
Excellent C and C++ programming skills.
Solid understanding of programming and debugging techniques, especially for parallel architectures.
Good understanding of system software/operating systems and computer architecture.
Experience with performance analysis, optimizations and benchmarking.
Outstanding communication and collaboration skills as this role might require significant interfacing with other teams within NVIDIA.

Nice To Haves

Understanding of embedded architectures and real-time operating systems & scheduling.
Strong mathematical fundamentals, including linear algebra and numerical methods.
Experience implementing algorithms in robotics, computer vision, and/or machine learning.
Software development experience with CUDA/GPGPU or any data parallel architectures.
Deep learning architecture/performance work on any HW accelerator, especially if on GPUs.

Responsibilities

Develop, maintain and optimize latency and throughput of NVIDIA’s L2/L3/L4 autonomous driving solutions.
Devise acceleration strategies and patterns to improve software architecture and its efficiency on our computers with multiple heterogeneous hardware engines while meeting or exceeding product goals.
Develop highly efficient product code in C++, making use of algorithmic parallelism offered by GPGPU programming (CUDA)/ARM NEON while following quality and safety standards such as defined by MISRA.
Collaborate with HW, product, OS, and safety teams to design next-gen products.