AI / Machine Learning Engineer II

What you'll do

• Lead end-to-end ML initiatives from data preparation and model development through production deployment and monitoring.
• Deploy and operate scalable ML solutions for batch or real-time inference with robust MLOps workflows.
• Design and analyze A/B tests and validation frameworks to measure incremental customer and business outcomes.
• Build propensity, response, uplift, recommendation, ranking, and contextual bandit models.
• Partner with engineering and product teams to integrate models into reliable production systems.
• Build agentic tools and reusable modules to automate and streamline ML development workflows.
• Process large-scale behavioral and transactional data using SQL, BigQuery, or Spark for feature engineering.

What we're looking for

• Five or more years of professional experience in applied machine learning, data science, ML engineering, applied statistics, or a related field.
• Experience building and evaluating models using large-scale behavioral, transactional, product, marketing, or customer data.
• Experience designing experiments, defining success metrics, measuring incrementality, and translating findings into business decisions.
• Experience partnering with engineering, product, and analytics teams to deploy and operate production ML systems and MLOps workflows.
• Strong Python skills and hands-on experience with common ML frameworks, supervised learning, model selection, and hyperparameter tuning.
• Strong SQL skills and experience with BigQuery, Spark, or similar platforms for data collection, cleaning, and feature development.
• Strong statistical reasoning and practical knowledge of A/B testing, causal measurement, and business-impact analysis.
• Experience with personalization, recommendation, ranking, uplift modeling, causal inference, contextual bandits, pricing, optimization, or lifecycle decisioning (preferred).