Machine Learning Engineer, Monetization AI/ML

Role Overview & Impact

OpenAI is looking for a Machine Learning Engineer to join our Monetization AI/ML team in San Francisco. You will develop intelligent machine learning systems and algorithmic models that optimize subscription intelligence, pricing dynamics, API token consumption forecasting, and enterprise compute allocation across millions of active API developers and ChatGPT Enterprise organizations.

Key Responsibilities

• Build, deploy, and evaluate machine learning models for user lifetime value prediction, churn propensity, and enterprise demand elasticity.
• Architect low-latency ML inference services integrated into OpenAI's payment and billing pipelines.
• Design rigorous online randomized controlled trials (A/B testing) to validate pricing adjustments and compute tier packaging.
• Partner with finance, product, and core research teams to balance financial sustainability with democratic AI accessibility.

Qualifications & Experience

• 3+ years of professional experience in applied machine learning, predictive modeling, or quantitative engineering.
• Strong proficiency in Python, PyTorch, and SQL; experience with modern data orchestration tools (Snowflake, Dagster, Ray).
• Sound theoretical understanding of causal inference, uplift modeling, and multi-armed bandits.
• BS, MS, or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

Compensation & Benefits

• Base Salary: $235,000 – $355,000 per year + substantial OpenAI Participation Units (equity).
• Comprehensive healthcare with 100% employer-covered premiums.
• Unlimited vacation, annual learning stipends, and flexible hybrid remote work options.