Bachelors degree or higher in Computer Science, Engineering, Mathematics, Statistics, or a related discipline.Substantial experience designing and managing ML workflows in Databricks, utilizing both provisioned clusters and serverless compute resources on AWS.Demonstrated advanced programming skills in Python and SQL for data engineering and pipeline development.Expertise using MLflow for experiment tracking, model management, and deployment within Databricks.Working knowledge of ML frameworks, libraries, and technologies (e.g. TensorFlow, PyTorch, scikit-learn, XGBoost, MLflow).Hands-on experience provisioning and optimizing compute resources for ML applications.Experience with workflow orchestration tools (e.g. Airflow, Lakeflow Jobs) for pipeline automation and scheduling.Practical experience operationalizing models and pipelines using GitHub for CI/CD, version control, and workflow automation.Strong knowledge of FinOps for cloud cost optimization. Effective collaboration and communication skills across technical and non-technical teams.
