Senior Software Control Integration Engineer - Autonomous Vehicles

We are now looking for a Senior Software Autonomous Vehicle Control Integration Engineer. As a Senior Software Control Integration 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, maintaining and integrating 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. Drive integration efforts of control functionality across different platforms, support troubleshooting of control and actuation issues in vehicles. Develop and maintain vehicle test suites to detect control integration problems, develop and maintain automated tests to ensure SW quality and prevent regressions. 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 8+ 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/Python) to product oriented implementation with C/C++. Experience in architectural design and 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. Experience of integrating, tuning, and validating prototype and/or production control software with application, driver, and vehicle network layers. Experience of development and/or usage of in-vehicle control software verification and calibration tools for autonomous vehicle applications. 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 as powertrain, steering system, brake system, advanced driver assist system, etc. Understanding of deep learning and neural network concepts 12+ years 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