What you'll be doingDesigning and maintaining data pipelines optimized for ML/AI workloads, including handling of large-scale, unstructured, and semi-structured data.Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models.Collaborating with Data Scientists and ML Engineers to understand data requirements for training, validation, and production deployment.Ensuring data quality, lineage, and governance meet standards required for AI/ML applications.Supporting MLOps practices by integrating data pipelines with model training, monitoring, and deployment workflows.Leveraging distributed processing frameworks (e.g., Spark, Databricks, Azure Synapse) for scalable ML data processing.
