• Design, develop, and own advanced deep learning models, including CNNs and transformer-based vision or multimodal architectures, for document verification use cases such as document classification, fraud detection, image quality assessment, field extraction, and authenticity checks. • Own ML solutions end to end, from data analysis and model training to deployment, monitoring, and continuous improvement in production. • Act as a technical point of contact for customers, leading technical deep dives, explaining model behavior, performance metrics, and tradeoffs, and supporting customer evaluations or escalations. • Translate customer, regulatory, and business requirements into clear modeling objectives, and communicate results effectively to both technical and non-technical stakeholders. • Partner closely with engineering and product teams to deliver scalable, reliable document verification systems.