• Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields. • 5+ years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration. • 3+ years of experience deploying, operationalizing, or supporting models in production or business-critical environments. • Strong hands-on experience with Python and SQL. • Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies. • Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management. • Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes. • Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders. • Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability. • Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment.
