Teams at Teleradiology Solutions (TRS)

Develop and evaluate deep-learning models for medical imaging classification, detection, and segmentation. Own scoped workstreams from dataset preparation through validation, documentation, and handoff. Build DICOM data pipelines, conduct clinical metric analysis and error analysis, collaborate with radiologists, and support production inference services using Python, Docker, and FastAPI. Work under senior guidance to deliver reproducible, clinically reliable AI systems.

Build and deploy operational machine learning algorithms for case routing, prioritization, forecasting, scheduling, and anomaly detection. Develop AI-enabled mobile features, optimize on-device inference, create production ML services with Python, Docker, and FastAPI, and establish data pipelines, testing, monitoring, and evaluation processes. Collaborate with operations, product, and engineering teams while using AI-assisted coding tools under senior engineering guidance.

Own end-to-end UX for clinical AI and healthcare products, including research, workflow mapping, interaction design, prototyping, usability validation, visual design, data visualization, design systems, accessibility, engineering collaboration, implementation review, and post-release refinement. The role focuses on complex, data-dense workflows used by radiologists, operations teams, and administrators.