• Architect and lead end-to-end ML/AI pipelines — including training, fine-tuning, experimentation, and deployment — setting technical standards across the team. • Design and own CI/CD pipelines for ML/AI workflows, including automated testing, model versioning, and continuous delivery to production environments. • Build and maintain scalable ML/AI infrastructure on cloud platforms. • Develop monitoring and observability frameworks to track model performance, data drift, and system health in production. • Develop tools and processes that leverage ML/AI to enhance user experience, extract insights from large datasets, and increase operational efficiency. • Research state-of-the-art ML/AI advancements and translate them into production-ready systems. • Design, build, and maintain APIs for exposing ML/AI models and data services to internal and external consumers. • Mentor junior and mid-level data scientists and engineers, conducting code reviews and driving engineering best practices across the ML organization. • Collaborate with cross-functional stakeholders to scope, prioritize, and deliver high-impact ML/AI solutions. • Perform other duties as assigned.