Computer Vision Engineer

About This Role

Design, develop, and implement computer vision and AI algorithms for robotics applications in a warehouse setting, focusing on segmentation, object detection, and classification. Optimize AI models for real-time deployment on autonomous robots in resource-constrained environments.

Responsibilities

• Design, develop, and implement computer vision and AI algorithms for segmentation, object detection, classification, localization, tracking
• Create and optimize AI models for warehouse-specific tasks such as inventory tracking, object picking, and path optimization
• Utilize deep learning frameworks (e.g., TensorFlow, PyTorch) for training and deploying machine learning models on embedded systems
• Integrate AI and computer vision algorithms with ROS (Robot Operating System) for real-time deployment on autonomous robots
• Perform data collection, labeling, and preprocessing for training AI models
• Optimize performance of AI models for resource-constrained environments, ensuring low-latency inference on embedded hardware
• Collaborate with robotics engineers to integrate AI and vision systems with sensors (cameras, LIDAR, etc.) and control systems
• Test and validate AI models in both simulation and real-world environments
• Document the development process, algorithms, and results for scalability and implementation

Requirements

• PhD or thesis-based Master's with 3+ years of experience in Computer Science, Electrical Engineering, Robotics, or related field
• 3+ years experience in AI/ML, perception, computer vision, localization for robotics applications
• Proficiency in developing and deploying AI/ML algorithms, including deep learning techniques for object detection and tracking
• Strong understanding of image processing, feature extraction, and 3D perception techniques
• Proficiency in Python, C++
• Experience with deep learning frameworks (TensorFlow, PyTorch)
• Experience with ROS (Robot Operating System) for real-time robotics applications
• Familiarity with deploying AI models on resource-constrained hardware and optimizing performance for real-time inference
• Experience in data collection, labeling, and preprocessing for AI training

Qualifications

• PhD (or thesis-based master’s with 3+ years of experiences) in Computer Science, Electrical Engineering, Robotics, or a related field
• 3+ years experience in domain of AI/ML, perception, computer vision, localization for robotics applications

Skills

* Required skills

Benefits