Calibration​/Localization Algorithm Engineer

Mandatory Requirement:

• Master's degree in electrical engineering, Electronics Engineering, Computer Science Engineering, or a related field.

• At least 5 years of hands-on experience in computer vision, image processing, and machine learning.

• Proficiency in programming languages such as C/C++, and Python.

• Experience with camera calibration techniques and tools (e.g., OpenCV, ROS).

• Strong understanding of perspective transformations and 3D reconstruction methods.

• Familiarity with Visual SLAM frameworks (e.g., ORB-SLAM, LSD-SLAM, RTAB-Map).

• Experience with automotive ADAS systems and sensor fusion.

• Knowledge of deep learning techniques for computer vision applications.

• Experience with real-time processing and optimization techniques.

• Experience with machine learning algorithm development for embedded ECUs

• Knowledge of product development engineering practices in automotive field

• Knowledge of embedded software development in C/C++ for 16-bit and 32-bit micro-controllers such as PPC microcontrollers, ARM Core, or DSP

• Working knowledge in structured engineering approach

• Working knowledge in development of portable, reusable and modular software in automotive environment.

• Experience in using a disciplined software development process based on ASPICE or CMMi process model

• Working knowledge of configuration management (preferably PTC/MKS), project monitoring and control techniques

• Strong background in mathematics, signal/image/video processing

• Experience with version control (Git) and requirement management tools (like PTC Integrity)

• Knowledge of structured problem solving (8D) methods and/or techniques

• Normal amount of sitting and standing, average mobility to move around an office and plant environment, able to conduct normal amount of work on a computer.

Responsibilities:

• Develop and enhance calibration algorithms for multi-camera systems.

• Implement procedures to correct lens distortion and camera misalignment.

• Develop algorithms for converting 2D images into 3D models and back to 2D projections.

• Apply mathematical techniques such as homography and projective transformations.

• Design and implement Visual SLAM algorithms for real-time localization and mapping.

• Utilize techniques for feature extraction, matching, and tracking.

• Integrate SLAM algorithms with data from other sensors (e.g., LiDAR, IMU) to enhance system performance.

• Continuously improve the performance of algorithm SW to ensure low latency and high accuracy in real-time, safety-critical automotive environments.

• Troubleshoot and resolve technical issues related to sensor data processing.

• Validate Algorithms using rea-world data and simulations.

• Work closely with hardware, software, and vehicle control engineers to integrate perception algorithms into Advanced Driver Assistance Systems (ADAS) and other safety features.

• Ensure all developed perception algorithms and safety systems comply with automotive industry safety standards, such as ISO 26262 for functional safety.