2.AI and Data Scientist at AOVs Underwater Robotics — NeverHard

Underwater Robotics Ltd. develops AI-enabled autonomous underwater vehicles for subsea inspection, monitoring, and data analysis. Our technology combines machine learning, computer vision, underwater sensing, and autonomous decision-making. Position Overview We are seeking an AI and Data Scientist to develop machine-learning models and data systems for autonomous underwater operations. The role will focus on computer vision, anomaly detection, sensor data, model training, simulation, and performance validation. The successful candidate will work closely with software developers, robotics specialists, and the founding team. Responsibilities Develop AI and machine-learning models for underwater inspection Build computer-vision systems for identifying corrosion, cracks, structural damage, and other anomalies Prepare and manage image, video, sonar, telemetry, and mission datasets Train, test, and improve models for low-light and low-visibility conditions Integrate AI models with onboard and cloud-based systems Document datasets, experiments, results, and model limitations Support simulation, controlled testing, and future field validation Qualifications Degree in Data Science, Artificial Intelligence, Machine Learning, Computer Science, Engineering, or a related field Strong Python skills and experience with PyTorch, TensorFlow, or similar frameworks Experience with computer vision, deep learning, anomaly detection, or sensor data Understanding of data preparation, model validation, and performance evaluation Strong analytical, research, communication, and documentation skills Experience with robotics, ROS or ROS2, reinforcement learning, simulation tools, edge deployment, sonar data, MLOps, or NVIDIA Jetson is an asset Reporting Structure The AI and Data Scientist will report to the Chief Executive Officer during the initial development stage and later to the Product Manager as the company grows. Underwater Robotics Ltd. is an equal opportunity employer. #J-18808-Ljbffr