Nu is a leading digital bank seeking a Lead Machine Learning Data Engineer for the AI Core Data Intelligence team. In this role, you will design and build scalable data ingestion pipelines, implement data quality monitoring, and transform raw data into features for foundation models. You will work across the machine learning lifecycle — from data labeling and model training to evaluation, deployment, and production monitoring — with robust quality controls. You will partner with product, compliance, and ML teams to ensure models are auditable, privacy-aware, and deliver measurable business value. You will help steward the data engineering backbone of AI Core, ensuring data is accessible, healthy, and properly tracked across our ML ecosystem. Your responsibilities include leading data infrastructure initiatives, mentoring team members, and contributing to hiring activities. Basic qualifications: typically 6+ years in machine learning engineering or data engineering; experience designing large-scale data ingestion pipelines with distributed frameworks (Ray, Spark or similar); strong applied ML background with training, tuning, and evaluation; Python proficiency; data quality and monitoring; excellent problem-solving and communication skills; leadership experience. Preferred qualifications: MLflow or similar tracking, foundation models knowledge, Dagster or Airflow, fintech experience, working in fast-paced distributed teams. Benefits include equity, comprehensive health coverage, extended parental leave, professional development resources, language learning, mental health sup

Nu is a leading digital bank seeking a Lead Machine Learning Data Engineer for the AI Core Data Intelligence team. In this role, you will design and build scalable data ingestion pipelines, implement data quality monitoring, and transform raw data into features for foundation models. You will work across the machine learning lifecycle — from data labeling and model training to evaluation, deployment, and production monitoring — with robust quality controls. You will partner with product, compliance, and ML teams to ensure models are auditable, privacy-aware, and deliver measurable business value. You will help steward the data engineering backbone of AI Core, ensuring data is accessible, healthy, and properly tracked across our ML ecosystem. Your responsibilities include leading data infrastructure initiatives, mentoring team members, and contributing to hiring activities. Basic qualifications: typically 6+ years in machine learning engineering or data engineering; experience designing large-scale data ingestion pipelines with distributed frameworks (Ray, Spark or similar); strong applied ML background with training, tuning, and evaluation; Python proficiency; data quality and monitoring; excellent problem-solving and communication skills; leadership experience. Preferred qualifications: MLflow or similar tracking, foundation models knowledge, Dagster or Airflow, fintech experience, working in fast-paced distributed teams. Benefits include equity, comprehensive health coverage, extended parental leave, professional development resources, language learning, mental health sup