Localization Algorithm Engineer

Job Title: Calibration/Localization Algorithm Engineer
Location: Auburn Hills, Michigan (Onsite)

Job Summary:

We seek a Calibration/Localization Algorithm Engineer with strong computer vision, image processing, and mathematical modelling expertise. The ideal candidate will focus on developing and optimizing algorithms for surround-view camera calibration, perspective transformations, and Visual SLAM (Simultaneous Localization and Mapping) to support our advanced driver assistance systems (ADAS).

Key Responsibilities:

• Develop and improve calibration algorithms for multi-camera systems.
• Correct lens distortion and camera misalignment issues.
• Create algorithms for 2D-to-3D image transformation and vice versa.
• Apply projective geometry techniques such as homography and perspective transformation.
• Design and implement real-time Visual SLAM algorithms for localization and mapping.
• Perform feature extraction, matching, and tracking.
• Integrate SLAM with sensor data (LiDAR, IMU) for enhanced accuracy.
• Optimize algorithm performance for low latency in real-time, safety-critical automotive systems.
• Troubleshoot and resolve issues related to sensor data and algorithm processing.
• Validate algorithms with real-world data and simulations.
• Collaborate with cross-functional teams for seamless integration into ADAS and safety features.
• Ensure compliance with automotive safety standards (e.g., ISO 26262).

Required Qualifications:

Education & Experience:

• Master s degree in Electrical Engineering, Electronics Engineering, Computer Science, or a related field.
• Minimum 5 years of experience in computer vision, image processing, and machine learning.

Technical Skills:

• Proficiency in C/C++ and Python.
• Experience with camera calibration tools (OpenCV, ROS).
• Strong knowledge of perspective transformations and 3D reconstruction.
• Familiarity with Visual SLAM frameworks (ORB-SLAM, LSD-SLAM, RTAB-Map).
• Experience with ADAS systems and sensor fusion.
• Understanding of deep learning applications in computer vision.
• Real-time processing and optimization experience.
• Embedded software development experience (16-bit/32-bit microcontrollers: PPC, ARM, DSP).
• Familiarity with automotive software development practices (e.g., ASPICE, CMMi).
• Working knowledge of version control (Git) and requirement management tools (e.g., PTC Integrity).
• Structured engineering and software development methodologies.
• Experience with configuration management tools (preferably PTC/MKS).
• Strong background in math, signal, and video processing.
• Understanding of structured problem-solving methods (8D).