Machine Learning Engineer, Growth

Details

The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments and other OpenAI products worldwide. The team works across the full funnel—from awareness and acquisition through activation, retention, and expansion—using experimentation, data science, machine learning, and product engineering. It partners with Product, Engineering, Data Science, Design, Finance, Lifecycle, and Growth Marketing, with a focus on measurement, privacy, reliability, and user trust.

The role involves building models and decision systems that optimize paid marketing investment for ChatGPT and other OpenAI products. This includes developing budget allocation and control algorithms that determine where to invest, how quickly to spend, and how to adjust as performance changes. The work combines machine learning, optimization, and experimentation to improve incremental growth and long-term user value within budget and efficiency constraints, from problem formulation and prototyping through deployment, evaluation, and ongoing operation.

This role is based in San Francisco, California, with a hybrid work model requiring three days in the office per week.

Responsibilities

• Build budget allocation algorithms to distribute investment across channels, campaigns, and markets using estimates of marginal returns while accounting for diminishing returns, uncertainty, and business constraints.
• Develop spend pacing and adaptive control systems that adjust budgets and spending rates as performance changes, balancing responsiveness with stability when feedback is delayed or noisy.
• Build spend limits, monitoring, and safe fallback behavior.
• Develop forecasts and models of conversion, long-term value, and saturation to determine where additional investment can have the greatest impact.
• Use simulations, backtesting, and online experiments to evaluate allocation and control policies.
• Partner with Data Science to measure incrementality and validate whether offline improvements translate into better investment outcomes.
• Build data pipelines, training and inference workflows, and integrations that turn model outputs into budget decisions.
• Establish data-quality checks, monitoring, and retraining with thoughtful treatment of privacy and consent.
• Partner with Growth Marketing, Data Science, Engineering, and Finance to define objectives and constraints, communicate tradeoffs, and improve investment decisions.
• Contribute to a diverse and inclusive culture based on collaboration, candor, and respect.

Requirements

• 5+ years of experience as a Machine Learning Engineer, Applied Scientist, Data Scientist, or in a comparable quantitative engineering role, or an equivalent record of impact.
• Experience building and operating production machine learning or quantitative decision systems, from problem formulation and data pipelines through deployment, experimentation, and monitoring.
• Strong software engineering skills.
• Proficiency in Python and SQL.
• Hands-on experience with machine learning frameworks and large-scale data systems.
• Strong foundations in machine learning and statistics.
• Experience applying optimization or control methods to decisions under uncertainty.
• Experience evaluating models or algorithms with noisy, delayed, or incomplete data.
• Ability to balance model quality, causal impact, and operational reliability.
• Ability to turn ambiguous goals into focused experiments, interpret mixed results, and communicate clear decisions with technical and non-technical partners.
• Collaborative working style and commitment to deploying AI responsibly.

Benefits

• Base salary of $381,000–$423,000 per year, plus equity.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, paid company holidays, office closures, and paid sick or safe time as required by law.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and meal delivery credits as eligible.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.
• OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.