Machine Learning Engineer II Recommendation Systems- Credit Karma

What you'll do

• Write data ETL code to read, clean, and transform raw feature sets into enriched training-ready datasets.
• Perform feature enrichment through aggregation logic such as computing rolling averages and merged histories across identity-stitched records.
• Train binary classification models using libraries like scikit-learn, XGBoost, or TensorFlow on properly assembled training sets.
• Build scalable data pipelines in a big data environment using tools such as BigQuery, Apache Beam/Dataflow, Spark, Flink, and Airflow.
• Implement models into production serving infrastructure and support model refresh workflows.
• Monitor production model performance and data quality; triage and resolve issues.
• Collaborate with data scientists to translate experimental notebooks into maintainable, production-grade code.

What we're looking for

• 3+ years of professional experience in software engineering, data engineering, or machine learning engineering.
• Strong proficiency in Python and experience with data libraries such as pandas, NumPy, scikit-learn.
• Solid understanding of data structures, algorithms, and writing clean, testable code.
• Experience with SQL and working with large-scale datasets.
• Familiarity with the end-to-end ML workflow including data preparation, feature engineering, model training, evaluation, and deployment.
• Ability to write bug-free, executable code for data ETL and model training tasks within a structured timeframe.
• Clear communication skills to articulate technical plans and explain decisions effectively.