Multiple technical interviews focused on programming, software engineering fundamentals, and the end-to-end MLOps lifecycle. Discussions included topics such as feature stores, model APIs, deployment strategies, CI/CD pipelines, infrastructure design, scalability, monitoring, and production best practices for machine learning systems. The process also included a pair programming exercise to assess problem-solving, coding skills, and collaborative development practices.