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

Mandatory Skills Description:

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 Skills Description:

• Experience in applying MLOps principles to financial domain.

• Familiarity with Databricks.