• Develop and deliver end‑to‑end machine learning solutions, including defining technical requirements, architecting scalable systems, and implementing monitoring, logging, and maintenance workflows. • Collaborate closely with engineers, product managers, clinicians, and cross‑functional partners to build new ML products and enhance existing systems. • Lead the design and implementation of MLOps frameworks, including pipeline development, CI/CD integration, drift detection, retraining workflows, and rollback strategies. • Monitor model performance in production, identify issues, propose remediation steps, and ensure strong test coverage and system reliability. • Utilize contemporary software engineering practices to implement scalable, secure, and maintainable AI/ML systems. • Develop and customize API integrations to enable seamless connectivity between cloud‑based systems and ML services. • Participate in architectural discussions to ensure ML platforms meet compliance, performance, and scalability standards.