Senior Software Control Engineer – Autonomous Vehicles
NVIDIA
Munich, Germany
vor 5 Tg.

We are now looking for a Senior Software Autonomous Vehicle Control Engineer. As an Autonomous Driving Control Engineer, you will work on state of the art autonomous vehicle technologies with leaders in AI / deep learning, computer vision, and vehicle control.

You will be responsible for developing and maintaining autonomous auto control algorithms and software. You will develop solutions for vehicle trajectory tracking, model predictive control, and vehicle state estimation.

You should have strong analytical skills, good communication, and interpersonal capabilities to work in a team and make a joint effort towards a common goal.

Prior knowledge about vehicle control, vehicle ECU, Drive-by-Wire systems, and in-vehicle network and autonomous vehicles are highly valued.

What you’ll be doing :

Contribute to the development related to vehicle dynamics and control and support other teams in such areas, e.g. ACC / LK, urban driving, trajectory planning, vehicle operation limit estimation, emergency maneuvers (collision avoidance, mitigation), etc.

Design technologies needed to build Autonomous Vehicle software stack, write new software modules from scratch that drive our vehicles.

Provide feedback for overall system design to product level : system architecture, failure mode, system redundancy, etc.

Build new performance offline and online benchmarks for vehicle control.

Define and build tools to tune our vehicle dynamics control and manage calibration updates for various vehicle types.

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

5+ years of work experience in relevant fields

Knowledge and hands-on application background in control theories, including at least three of the following fields : classical control, modern control, nonlinear control, MPC, optimal control, robust control, sliding mode control.

Understanding of state estimation techniques such as Luenberger observer, kalman filter, etc.

Ability to develop vehicle models and, perform parameter identification and benchmarking.

Knowledge of high-level algorithm design and prototyping in simulation environments (Matlab / Simulink) to product oriented implementation with C / C++.

Experience in software development with C / C++ for real-time embedded control systems, such as vehicle ECU systems.

Understanding of test and verification methodologies for automotive software, know-how in writing unit 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

Experience in developing and launching vehicle safety critical control system products such powertrain, steering system, brake system, advanced driver assist system, etc.

Understanding of deep learning and neural network concepts

Engineering experience at automotive OEM, tier-1 supplier or autonomous driving start-ups

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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