Nvidia is hiring a
System Software Engineer, Planning and Control, Autonomous Vehicles
NVIDIA has continuously reinvented itself over two decades. NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. This is our life’s work — to amplify human imagination and intelligence.
NVIDIA China Automotive Software Solution team is searching for a Senior Planning and Control Software Engineer to help us bring NVIDIA's Self Driving solution out to the world and optimize it for China market. As core member of our team, you will be located at NVIDIA Shanghai or Beijing office. You will take the lead for validating, adapting, and improving NVIDIA’s Autonomous Vehicle software stack in China. You should also have strong communication, good teamwork passion, and analytical skills. Rich development and validation experience in Active Safety, L2/L2+, Parking system of driving car, or robotics planning and control modules are highly valued. Familiarity with deep learning / artificial intelligence is a bonus.
What you will be doing:
In depth understanding of L2/L2+ Driving and code implementation in NVIDIA AV software stack.
As a software expert of Planning and Control module in our team, you should work close with different teams to be in-depth analysis of the root cause of L2/L2+ function issues found in China.
You will have chance to collaborate with other algorithmic teams to adapt planning & control architecture and write code logic implementation based on China scenarios.
What we need to see:
BS or higher in Computer Engineering, Computer Science, Automotive Engineering, Electrical Engineering or related engineering fields or equivalent experience.
Familiar with control system designs and planning algorithms, for example: classical feedback controllers, optimal control, occupancy grids, Dijkstra search, A*, Random Root Tress (RRTs), etc.
Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures.
Be proficient in C, C++, and scripting languages such as Python in Linux or QNX environment.
2+ years of experience in motion planning/path planning/control theory, or related field.
Ways to stand out from the crowd:
Experience developing real-time planning algorithms on an embedded platform.
You are a self-starter with path planning and control in a shipping product context.
Previous experience with Deep Learning, training neural networks, and building inference solutions.
Strong leadership and interpersonal skills, with the ability to drive alignment across different teams.
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