MLOps engineer

Project description Work alongside software engineers and data scientists to ensure that quantitative research models are effectively developed, tested, and deployed in production environments. Responsibilities Creation and maintenance of CI/CD pipelines for efficient deployment of ML models Data management - e.g. connect with data sources and create ETL pipelines, cleanse the data, create datasets for model retraining Create pipelines for automated model testing SKILLS Must have Strong knowledge of Python and familiarity with relevant libraries, e.g. scikit-learn, TensorFlow, and PyTorch. Data - SQL, ETL, Pandas. Containerization (Docker / Kubernetes) and Cloud (AWS). Nice to have Experience in applying MLOps principles to financial domain. Familiarity with Databricks. #J-18808-Ljbffr