• Design and implement MLOps pipelines to automate model training, deployment, monitoring, and management • Lead/mentor a team of MLOps Engineers, fostering an inclusive and collaborative environment that encourages innovation and continuous learning • Collaborate with Data Scientists and ML Engineers to ensure models are production-ready, scalable, and maintainable • Develop strategies for model versioning, testing, and deployment to facilitate a seamless and efficient development lifecycle • Monitor model performance and data drift, implementing automated alerts and processes for model retraining and optimization • Develop and maintain platforms and applications that serve as foundational components for robust and scalable ML pipelines • Stay at the forefront of MLOps trends, tools, and technologies, integrating new approaches to enhance our ML operations and infrastructure