ML Ops expert

ML Ops expert Location: Santa Clara CA – post COvid Design, develop, deploy, and maintain production-grade scalable data transformation, machine learning and deep learning code, pipelines; manage data and model versioning, training, tuning, serving, experiment and evaluation tracking dashboards.Manage ETL and machine learning model lifecycle: develop, deploy, monitor, maintain, and update data and models in production.Build and maintain tools and infrastructure for data processing for AI/ML development initiatives.Develop ETL pipelines, tools and processing jobs for data cleansing, labeling and analysis.Experience deploying machine learning models into production environment.Strong DevOps, Data Engineering and ML background with Cloud platformsExperience in containerization and orchestration (such as Docker, Kubernetes)Experience building/operating systems for data extraction, ingestion and processing of large data setsExperience with MLOps tools such as MLFlow and KubeflowExperience in Python scriptingExperience with CI/CDExperience with ML training/retraining, Model Registry, ML model performance measurement using ML Ops open source frameworks