In our DAT2 (Driver Assistance Technologies 2) program, our Safety Electronics team designs and develops hardware and functional models that provide Best in Class behavior for features like Adaptive Cruise Control, Automatic Emergency Braking, Cross Traffic Alert, Active Park Assist and 360 Camera Systems.


  • Lead the development and implementation of algorithms related to imaging, image processing and vision.
  • Support the development of active safety features.
  • Lead the development of algorithm specifications, FMEAs, robustness disciplines and DVP.
  • Understand the performance requirements for the sensing system, establish feature model to operate with the sensor performance envelop and  establish procedures to verify performance both quantitatively and subjectively.
  • Establish algorithm objectives and ensure system operation to meet the objectives through structured component, sub-system, and system level test methodologies.
  • Work with the Hardware in the Loop Team to establish CAE procedures to reduce dependence on vehicle level testing.
  • Support Sign off of algorithm performance per a given vehicle

Basic Qualifications:

  • Bachelor’s Degree in Software, Electrical, Mechanical, Aerospace or Controls Engineering
  • 2+ years experience in software development in C or C++

Preferred Qualifications:

  • An understanding of embedded software development
  • Experience in imaging, image processing and/or computer vision to support active safety features
  • Experience mapping image processing algorithms to HW (DSP, SIMD, NEON, GPU, FPGA)
  • Understanding of ISP algorithms, human vision system and image quality metrics
  • Familiarity with open source vision, sensor fusion and machine learning frameworks (OpenCV, ROS, Tensorflow, PyTorch, Caffe2, scikit-learn)
  • Simulating vision and/or Lidar sensors for algorithm training, validation and testing
  • Design and development of vision applications
  • Python, ipython, jupyter notebooks
  • Git, Github, Jira, Agile, Misra C\C++, ISO 26262