Responsibilities: Define and implement the technical MLOps strategy and roadmap for the position Serve as a technical leader and mentor for MLOps engineers Design, build, and maintain scalable and reliable machine learning & CI/CD pipelines Ensure the efficient deployment, monitoring & Governance of AI models in production Collaborate with data scientists and engineers to optimize model performance and deployment Establish and enforce best practices for MLOps, including version control, model governance, and monitoring Evaluate and implement new MLOps tools and technologiesRequired Skills:+8 years of relevant experience in Data Science or a related field 2 years of them in the MLOps field Extensive experience in designing and implementing MLOps strategies and pipelines Deep expertise in on-prem platforms and containerization technologies (e.g., Docker, Kubernetes) Strong proficiency in programming languages like Python and scripting languages Experience with CI/CD & MLOps tools as well as different ML frameworks Strong understanding of data engineering and software development principles Excellent communication and technical documentation skills Ability to work effectively in a complex and dynamic environmentDesirable Skills: Experience with feature stores and model registries Knowledge of data governance and compliance requirementsExperience with different data platforms (Cloudera, Teradata, etc..)