Machine Learning Engineer, Core Experimentation

What you'll do

• Set the technical roadmap for Generative Insights and Predictive Experimentation, from prototypes to production.
• Build systems for learning across historical experiments, predicting impact and uncertainty, and evaluating predictions against live outcomes.
• Create reliable, privacy-conscious data pipelines and production workflows, including approval-gated actions and human review.

What they ask for

• Hands-on experience across the ML lifecycle, including dataset design, training or adaptation, evaluation, deployment, monitoring, and iteration.
• Strong software engineering fundamentals and ability to build production systems in Python.
• Strong grounding in machine learning, statistics, computer science, or a related field through formal study or equivalent practical experience.
• Understanding of experimentation and statistical reasoning, including the difference between predictive accuracy and causal validity.

Nice to have

• Experience leading ambiguous 0-to-1 production ML products measured by real-world decision quality.
• Depth in one or more of LLM and retrieval systems, ranking or recommendation, forecasting or anomaly detection, causal ML or experiment analysis, or simulation.

Pay

$437K – $485K USD total pay

Tools

Python

AI focus

Builds ML, retrieval, and LLM-powered systems for experimentation insights and impact prediction, with calibrated uncertainty, provenance, privacy protections, and human approval boundaries.