Machine Learning Engineer, Core Experimentation

About this role

Lead the design and development of ML-powered experimentation and insights systems at OpenAI's Statsig platform, building end-to-end production systems that help product teams make evidence-based decisions. You'll combine ML modeling, LLM systems, statistical methods, and simulation to generate traceable, calibrated insights while maintaining safety and transparency in high-stakes product decisions.

What you'll do

• Set and execute technical roadmap for generative insights and predictive experimentation from prototypes through production
• Build cross-experiment learning systems that retrieve historical data, detect patterns, and generate hypotheses with clear evidence
• Develop predictive models and simulation workflows to estimate impact, affected segments, and regression risk before live experiments
• Create high-quality datasets and retrieval pipelines with strong lineage, privacy controls, and data-quality guarantees
• Establish rigorous evaluation through backtests, calibration, drift monitoring, and prediction-to-outcome comparisons
• Partner with data science and product teams on experiment design, causal inference, and sequential decision-making

What they're looking for

• Machine learning systems design and lifecycle management
• Python and production software engineering fundamentals
• LLM and retrieval systems
• Statistical methods and causal inference
• Experimentation and A/B testing design
• Data pipeline and feature engineering
• Forecasting, simulation, or anomaly detection
• Ranking or recommendation systems