Engineering Manager, Planning and Decision Making - Autonomous Vehicles
Engineering Manager, Planning and Decision Making - Autonomous Vehicles
22/12/2021
Our team is building the core algorithms and software for Nvidia's self-driving vehicle solution. We are now looking for an Engineering Manager to join our Planning and Control team, and focus on Planning and Decision Making. As a Manager in the team, you will work on state of the art autonomous vehicle technologies with leaders in planning, prediction, AI /deep learning, control, state estimation, modeling, simulation, and evaluation. What you’ll be doing: Lead a team of engineers developing software and algorithms for autonomous driving Decision Making and Planning Drive the architecture, implementation, evaluation and validation of algorithms and software to support various driving functions Work together with multiple teams to integrate new software elements into the driving stack Evaluate and negotiate product requirements, ensure the team's work is aligned with high-level expectations Drive the debugging and fixing of driving issues uncovered in simulation and real-world driving, and help communicate challenges and mitigation plans Define a roadmap and an execution plan for the development, integration and testing of Planning and Decision Making solutions for autonomous vehicles Most importantly, work on groundbreaking and innovative technology, tackle difficult problems, and help build a world-class system
What we need to see: BS, MS, or higher degree in Mechanical Engineering, Electrical Engineering, Computer Science or equivalent experience 10+ years of relevant experience, at least 6+ years managing a team Strong analytical skills, good communication, and interpersonal capabilities to work in a team and make a joint effort towards a common goal Prior experience as a tech lead working to tackle Decision Making and Planning challenges in the fields of robotics or autonomous vehicles Solid software programming skills using C/C++ and a scripting language such as Python Understanding of test and verification methodologies for production software, know-how in writing unit level and system level tests Ways to stand out from the crowd: Hands-on experience in autonomous vehicle or advanced driver assist system development such as lane keeping, adaptive cruise control, etc. Background in automotive safety concept, failure mode, common analysis tools such as FMEA Understanding of deep learning and neural network concepts PhD with relevant experience Academic and commercial groups around the world are powering a revolution in artificial intelligence using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing. Intelligent machines powered by AI 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. The era of AI has begun.
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