Machine Learning Engineer, Growth
OpenAI · San Francisco
Frontier labremotesenior$381k–$423k
At a glance
Highlights
- Build budget allocation algorithms optimizing paid marketing for ChatGPT.
- Develop adaptive spend pacing systems that react to noisy delayed signals.
- Model conversion, saturation and long-term value to guide next-dollar spend.
What they offer
- Equity
- Relocation assistance for eligible employees
Ideal candidate
A quantitative engineer who thrives on ambiguous growth problems, blending ML, optimization and experimentation to drive reliable, high-trust investment decisions end-to-end.
Requirements
- 5+ years as Machine Learning Engineer, Applied Scientist, Data Scientist or comparable quantitative engineering role
- Experience building and operating production ML or quantitative decision systems through deployment and monitoring
- Strong software engineering skills with proficiency in Python and SQL and ML frameworks and large-scale data systems
- Strong foundations in machine learning and statistics with optimization or control for decisions under uncertainty
- Experience evaluating models with noisy, delayed or incomplete data balancing quality, causal impact and reliability
- Ability to turn ambiguous goals into focused experiments
- remote policy
- Hybrid, 3 days in office per week
Lab profile
About OpenAI
Builds safe frontier AI models and products like ChatGPT for broad benefit.
What they build
- ChatGPT
- OpenAI API
- Frontier AI models
Known for
- Frontier-scale distributed ML training
- Massive GPU fleet and data center operations
- Exabyte-scale data lakes and streaming
- AI alignment and safety research
Key facts
- Operates one of the world's largest GPU fleets
Posted · Last seen