At C-CORE, we are committed to investing in people and creating a dynamic and rewarding employment experience. We are seeking an AI Engineer to join our COREsight Team. This position is based in St. John’s, NL. If you have a passion for complex design solutions, hands-on development, and contributing to cutting-edge R&D projects from concept to commissioning, this opportunity may be for you. Are you enthusiastic about engineering, attentive to detail, and motivated to support a diverse team of professionals in a dynamic setting? If so, we want you on our team! About C-CORE C-CORE conducts R&D and provides research-based advisory services, delivering innovative engineering and technology solutions to national and international clients. For over 50 years, we have built a world-class team of professionals in Remote Sensing and Oceans & Energy. We are global leaders in Earth Observation and geospatial intelligence, with our flagship platform COREsight driving major contracts in defense, environmental monitoring, and advanced R&D. Position Overview COREsight is a Maritime Domain Awareness (MDA) platform that fuses satellite imagery (SAR, optical), AIS vessel tracking,



and RF signal detection into a real-time analyst environment used by government and defence customers, including an active NATO-affiliated deployment. We are looking for an AI Engineer to work on the ML core of the platform — the models and pipelines that turn raw satellite and sensor data into actionable maritime intelligence. This is a hands-on ML role, not front-end: you’ll be working on target correlation algorithms, data fusion pipelines, geospatial foundation models, and the production ML pipeline (MLOps) that supports them, reporting to the Director, COREsight. Key Responsibilities Develop and refine ML models for maritime target correlation, integrating satellite imagery, AIS, and RF data sources Research, evaluate, and adapt geospatial foundation models for remote sensing and Earth observation tasks relevant to MDA Design and maintain to MLOps infrastructure: model registry, experiment tracking, automated retraining, validation, and staged deployment Evaluate model performance against operational metrics and support continuous model monitoring in production Document methods, experiments, and results to support reproducibility and knowledge

📌 Ai Engineer, Intermediate (St. John's)
🏢 C-CORE
📍 St. John's