We are seeking a talented AI Engineer with strong skills in C++ and Python to develop and optimize software pipelines for visual AI applications. This role involves integrating and building upon open-source components to create scalable, efficient pipelines that power computer vision and visual recognition systems. You will collaborate closely with data scientists, machine learning engineers, and software developers to design solutions that drive innovation in visual AI. Key Responsibilities: Design, develop, and deploy robust software pipelines for visual AI applications, using open-source components and frameworks. Write, test, and optimize code in both C++ and Python to ensure high performance and reliability in real-time visual AI processing. Integrate and adapt open-source libraries and frameworks (e.g., OpenCV, PyTorch, TensorFlow) to meet project requirements. Build efficient data processing and model inference pipelines, enabling scalable deployment in production environments. Collaborate with data scientists to implement data preprocessing, augmentation, and model training pipelines for visual data. Troubleshoot and optimize performance of the visual AI pipelines, addressing latency, memory usage, and accuracy challenges. Develop and maintain documentation, including pipeline architecture, API specifications, and best practices. Keep abreast of advancements in computer vision and visual AI, evaluating new open-source tools and techniques to enhance pipeline capabilities. Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Computer Vision, or a related field, or equivalent practical experience. Strong experience in software engineering, with proficiency in C++ and Python programming languages. Strong understanding of computer vision principles and experience in visual AI applications, including object detection, image classification, and segmentation. Hands-on experience with open-source visual AI libraries and frameworks (e.g., OpenCV, PyTorch, TensorFlow, ONNX). Familiarity with developing end-to-end pipelines, including data preprocessing, model training, inference, and deployment. Knowledge of performance optimization techniques, such as parallel processing, GPU acceleration, and memory management. Ability to work with cross-functional teams, including data scientists and DevOps engineers, to integrate visual AI pipelines into broader systems. English required Preferred Skills: Experience with containerization tools (Docker) and cloud platforms (AWS, GCP, Azure) for deploying visual AI applications. Familiarity with machine learning model optimization techniques, such as quantization, pruning, and distillation. Knowledge of MLOps best practices, including CI/CD for machine learning and model monitoring. Contributions to open-source projects, especially in the computer vision domain.