Verification and Validation Engineer

About the role

The ADAS Sensing Systems Validation Engineer validates and continuously improves the performance of ADAS sensing systems across Ford’s vehicle lineup by developing and executing validation methods, defining use cases and functional requirements, collaborating with hardware, software, systems engineering and supplier teams, leveraging HIL/CAE methodologies, and driving continuous improvement of V&V processes.

About the company

Ford Motor Company is a global automotive leader that designs, manufactures and sells vehicles worldwide, investing heavily in advanced driver‑assistance (ADAS) technologies and offering a range of employee benefits and career development opportunities.

Requirements

• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Robotics, Controls, Aerospace Engineering, Computer Science or related field.
• 2+ years validation/test engineering experience in a professional or educational setting.
• Experience with data collection and analysis in laboratory, HIL, and vehicle test environments.
• General knowledge or experience developing/testing ADAS features and sensing systems using radars, cameras, lidars, ultrasonic sensors or related vehicle systems.
• Proficiency with Vector, CANalyzer, and CANape tools.
• Strong analytical and creative problem‑solving skills.
• Master’s degree in Electrical Engineering, Mechanical Engineering, Robotics, Controls, Aerospace Engineering, Computer Science or related field (preferred).
• Experience leading validation and verification of ADAS sensing systems (preferred).
• Experience with computer vision and radar tracking of humans, vehicles, static roadway obstacles or other road objects (preferred).
• Experience with computer vision detection and tracking of signs, lights, lanes or other key artifacts (preferred).
• Understanding of embedded hardware and software design (preferred).
• Experience reviewing, categorizing, and analyzing field data to determine error states/failure modes (preferred).
• Experience developing, conducting, observing, and reporting statistically relevant verification and validation methods across a global population (preferred).
• Experience with Mobileye EyeQ technology (preferred).
• Exposure to vehicle attribute development such as Vehicle Dynamics, NVH, Package, Performance/FE (preferred).
• Project management or integration role experience, leading and directing team members (preferred).
• Experience with failure mode analysis techniques (preferred).
• Understanding of Kalman filtering, vehicle dynamics, and linear/nonlinear control methods (preferred).
• Software engineering and algorithm development experience in C, C++, Python, MATLAB (preferred).