Collaborate with cross-functional teams to transition AI/ML models from prototypes into scalable, production-ready systems. Build, deploy, and maintain CI/CD pipelines for machine learning models, ensuring reproducibility, scalability, and reliability. Design and implement cloud-based infrastructure (AWS, Azure, or equivalent) for training, inference, and monitoring of AI models. Automate repetitive ML lifecycle tasks, improving efficiency and consistency in retraining and deployment workflows. Integrate large language models (LLMs), generative AI, and NLP solutions into IMO Health’s Clinical AI products, with a focus on unstructured clinical data. Develop scalable inference pipelines and APIs to deliver AI capabilities into customer-facing solutions. Apply containerization (Docker, Kubernetes) and Infrastructure-as-Code to manage production environments. Participate in system design and architecture discussions, bringing expertise in MLOps and AI deployment best practices. Ensure performance, reliability, and security of deployed models, optimizing for latency, throughput, and cost. Collaborate in an Agile environment with cross-functional teams, aligning technical solutions with product and business goals.