Ford’s Research and Advanced Engineering team takes new ideas from theory to reality. Every day, we develop advanced energy management and propulsion technologies, create cutting-edge materials and manufacturing processes, and curate world-class cabin experiences that redefine what it means to drive a Ford.

The Sensing Technologies and Algorithms team is central to Ford’s vision of achieving industry wide leadership and is spearheading the process of discovery through a transformative adoption of sensors, algorithms, and AI-ML across all engineering functions within the Ford product landscape. The multidimensional team of experts is tasked with conducting applied research in the domains of interior and exterior sensing systems, technologies, capabilities, architectures, and features. To this end, the team is looking for highly qualified and motivated individuals who are willing to work on challenging, multi-functional problems requiring discovery and fundamental research for delivering transformative and disruptive technology. 

You'll have... 

Master of Science degree in Electrical Engineering, Computer Engineering, Computer Science, or Robotics or related field 3+ years of demonstrated hands-on experience in developing and implementing camera, radar, or Ultra-wideband (UWB) 1+ years of hands-on experience in developing signal processing, data analysis, or computer vision solutions. 1+ years of product development and system integration.

Even better, you may have…

PhD degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics or related field 5+ years of demonstrated hands-on experience in developing and implementing camera, radar, Ultra-wideband (UWB), or lidar hardware 2+ years of hands-on experience in developing signal processing, data analysis, or computer vision solutions. 2+ years of product development and system integration. Experience with designing and testing internal sensor hardware components such as camera components or UWB antennas. Experience with pairing sensors with embedded or low-power computer hardware such as SOCs or FPGAs Experience in AI/ML techniques for object detection and tracking, scene understating, multi-modal perception, and sensor fusion. Excellent problem-solving skills, innovative thinking, and ability to identify, propose and lead new research projects that have a clear near or far value add. Passionate about staying abreast of large-scale challenges and disruptive changes in sensing technologies and their real time realizations for quickly establishing applicability to Ford engineering problems to create/contribute to the Ford’s strategic and leadership vision.

This role requires taking the lead in exploring new sensor hardware, performing data analysis, developing sensing algorithms, proposing test plans, evaluating sensor performance, delivering proof-of-concept demonstrations, and implementation readiness process. The ideal candidate will have expertise in the fundamentals of one or more sensing technologies as well as experience developing algorithms with data-driven evaluation techniques. The candidate will have a proven track record of developing and progressing a structured research portfolio to take sensing technologies from ideas to proven concepts and application readiness.

Grow and maintain expertise in state-of-the-art camera, radar, UWB, and/or lidar hardware advancements. Identify opportunities for innovating automotive sensing suites to improve quality and reduce costs. Develop sensing solutions for interior sensing features such as Child Presence Detection, Driver State Monitoring, and Cabin Monitoring as well as exterior sensing features such as Proximity Detection, 360° surround view, and automated driving.  Collaborate with cross functional teams including strategy and planning, application/product engineers, and others in defining data needs, validation of solutions against real-world application benchmarks, quality and robustness checks and continuous improvement. Through self-learning and deep research identify novel sensing solutions that can apply to new problem statements with atypical feature constraints.  Publish internally and externally to engage in knowledge dissemination through teaching, mentoring, and seminars as well as through any Ford learning and development programs.  Develop a research portfolio for progressing external research with leading universities.