Embedded ADAS Systems Engineer

Job Title: Embedded ADAS Systems Engineer
Location: Auburn Hills, Michigan (Onsite)
Duration/Term: Long Term Contract

Job Summary: We are seeking an Embedded ADAS systems engineer to develop and optimize algorithms for multi-camera calibration, perspective transformations, and Visual SLAM (simultaneous localization and mapping). This role requires expertise in computer vision, image processing, and mathematical modeling to improve precision and reliability in advanced driver assistance systems (ADAS).

Key Responsibilities:

• Develop and refine multi-camera calibration algorithms.
• Implement lens distortion correction and camera misalignment adjustments.
• Design algorithms for 2D-to-3D conversions and perspective transformations.
• Apply homography and projective transformations to improve spatial accuracy.
• Build Visual SLAM algorithms for real-time localization and mapping.
• Utilize feature extraction, matching, and tracking for sensor data analysis.
• Integrate SLAM algorithms with LiDAR and IMU sensor data for enhanced performance.
• Optimize algorithms for low latency and high precision in real-time safety applications.
• Troubleshoot and resolve sensor data processing issues.
• Validate algorithms with real-world data and simulations.
• Collaborate with hardware, software, and vehicle control engineers to integrate perception systems into ADAS and safety features.
• Ensure compliance with ISO 26262 automotive safety standards.

Required Skills & Experience:

• Master s degree in Electrical Engineering, Electronics Engineering, or Computer Science.
• 5+ years of hands-on experience in computer vision, image processing, and machine learning.
• Proficiency in C/C++ and Python programming languages.
• Experience with OpenCV, ROS, and camera calibration techniques.
• Strong understanding of perspective transformations and 3D reconstruction.
• Familiarity with Visual SLAM frameworks such as ORB-SLAM, LSD-SLAM, RTAB-Map.

Technical Knowledge:

• Expertise in automotive ADAS systems and sensor fusion.
• Knowledge of deep learning techniques for computer vision applications.
• Experience with real-time processing and optimization techniques.
• Familiarity with machine learning algorithm development for embedded ECUs.
• Knowledge of embedded software development in C/C++ for microcontrollers.
• Experience with ASPICE/CMMi software development processes.
• Proficiency in Git version control and requirement management tools (PTC Integrity).
• Background in structured engineering approaches and problem-solving techniques (8D).

Key Skills: Computer vision, image processing, machine learning, Visual SLAM, ADAS integration, automotive safety standards, real-time algorithm optimization, C/C++, Python, OpenCV, ROS, sensor fusion, LiDAR/IMU integration, perspective transformations, structured problem-solving, Git, ASPICE.

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