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

• 1. Strong knowledge of Python and familiarity with relevant libraries, e.g. scikit-learn, TensorFlow, and PyTorch. 2. Data - SQL, ETL, Pandas. 3. Containerization (Docker / Kubernetes) and Cloud (AWS).

Nice to have

• Experience in applying MLOps principles to financial domain. • Familiarity with Databricks.