Robotics Engineer

Your Mission This position is responsible for designing, developing, fine-tuning, and optimizing deep learning models for robotics and quality inspection applications. He/She will contribute to the development of advanced robotics algorithms for object detection, recognition, segmentation, pose estimation, and motion planning. What To Expect Demonstrate strong interest and expertise in, but not limited to, the following domains: 2D/3D object recognition, segmentation and pose estimation, feature extraction, vision-based robot control Design, develop, and optimize deep learning models (e.g., convolutional neural networks and transformers) to process and analyze sensor data from various modalities (e.g., vision and depth sensors) for object segmentation and pose estimation in robotic applications. Evaluate and calibrate various sensors to ensure the collection of high-quality and accurate data for AI model training. Validate the performance of implemented algorithms using real-world car part datasets. Collaborate with robotics engineers to integrate AI solutions into robotic systems and ensure seamless operation. Prepare and maintain technical documentation, including technical reports, program code, and setup manuals. What You'll Bring Master's or Ph.D. degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, or a related discipline, with more than 5 years of relevant industry experience. Strong foundation in deep learning techniques, particularly convolutional neural networks (CNNs) and transformers. Expertise in deep learning frameworks (e.g., TensorFlow and PyTorch) and 2D/3D computer vision libraries (e.g., OpenCV and PCL). Knowledge of data quality requirements for various AI training tasks and data acquisition protocols. Strong understanding of robot kinematics, dynamics, and control theories (e.g., PID Control, Model Predictive Control, and Impedance Control). Proven experience in developing and deploying custom pick-and-place or pick-and-assemble applications. Hands-on experience with industrial robot arm controllers, sensor integration, and robotic workcell setup. Ability to evaluate and shortlist candidate solutions or sensors based on technical feasibility, performance, and cost considerations. Good understanding of pose estimation, grasp planning, robot motion planning algorithms, and robotic simulation platforms. Proficiency in programming industrial robots using manufacturer-specific programming languages, as well as C, C++, C#, and Python. Familiarity with ROS 1/2, Linux operating systems, and other real-time control frameworks or software tools. Any patents, publications, specialist certifications, or awards related to multimodal processing will be considered an added advantage.