Computer Vision Engineer

Job Description

Job description Company Description Doozy Robotics designs flexible and intelligent autonomous mobile robots for the industry. The company offers Humanoid and Autonomous Robots that assist in both commercial and industrial applications. Doozy Robotics is at the forefront of innovation, developing advanced robotics solutions tailored to enhance efficiency and productivity. As a fast-growing leader in the robotics field, Doozy Robotics provides cutting-edge technologies and solutions to meet the evolving needs of various industries. Role Description Key Responsibilities Perception System Development: Design and implement perception algorithms for object detection, tracking, and scene understanding using data from cameras, LiDAR, radar, and other sensors. Sensor Fusion: Develop sensor fusion techniques to integrate data from multiple sources, enhancing the accuracy and reliability of environmental perception. Computer Vision: Apply computer vision methodologies for real-time image processing, feature extraction, and pattern recognition in dynamic environments. AI/ML Model Development: Build and train machine learning models for tasks such as semantic segmentation, depth estimation, and anomaly detection. Robotics Integration: Collaborate with robotics engineers to integrate perception systems into autonomous platforms, ensuring seamless operation in real-world scenarios. Collaboration: Work closely with cross-functional teams to develop AI-powered vision systems, contributing to the advancement of autonomous technologies. Qualifications Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field. Experience: 3+ years of hands-on experience in AI/ML development, computer vision, and sensor fusion. Technical Skills: Proficiency in programming languages such as Python, C++, and ROS. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Familiarity with sensor technologies (e.g., LiDAR, radar, cameras) and their integration. Knowledge of SLAM, 3D reconstruction, and path planning algorithms. Soft Skills: Strong problem-solving abilities, effective communication, and a collaborative mindset.