Autonomous Vehicle System Engineer

Ford Otosan

*Experience in Perception / Computer Vision
*Background in Artificial Intelligence / Machine Learning
*Software/firmware development in one or more languages/platforms/libraries (C/C++, VHDL/Verilog, MATLAB, CUDA, OpenCL, ROS)
*Experienced on Unit Testing
*Working Knowledge of Software Quality and Development Processes
*Preferably experienced on embedded operating systems (QNX, GHS Integrity, etc.)
*Preferably experienced on Ethernet, FlexRay, CAN
*Preferably experienced on Automotive Standards (AUTOSAR, Automotive-Spice L2/L3, ISO 26262)
*Preferably experienced on Path Planning, Localization and Vehicle Motion Control
*Preferably experienced in automotive hardware, software test and validation HIL/SIL/MIL (dSpace, CarMaker, PreScan, etc.)
*Undergraduate or advanced degrees (MSc, PhD) from Electrical & Electronics, Control, Mechatronics, Computer Engineering Department

İŞ TANIMI

Do you want to be at the technological forefront of Autonomous Vehicle Development? This is your opportunity to join the ‘AV Systems & Software Engineering Team’ and take part in the development of Ford Otosan’s Heavy Duty Truck Autonomous Driving projects. 

Automated driving requires the development and deployment of advanced electronic hardware, software design, and sophisticated control strategies. Engineers in this organization are responsible for:

• Development of different levels of heavy duty autonomous driving functions ranging from Level 2 up to Level 4
• Develop and maintain software to drive the truck, given various sensor inputs including Cameras, LIDAR, RADAR, GPS and IMU
• Benchmarking and selection of different sensors from different suppliers and technology start-ups
• Development of engineering requirements for sensor integration and E/E architecture development
• Develop and maintain recognition algorithms based on sensor raw data and object data
• Develop data fusion algorithms for fail operational systems
• Develop advanced decision making, motion planning and low-level control algorithms of different AV features
• Working on different validation techniques of AV features
• Support safety analysis according to ISO 26262 Functional Safety, including item definition, hazard and risk assessment as well as ASIL decomposition to derive an optimal fail-operational architecture
• Working jointly with cross-functional teams in the adaptation of existing vehicle subsystems and components for autonomous vehicle applications