Machine Learning Engineer, Core Experimentation

Job summary

Responsibilities

This is an end-to-end, 0-to-1 role. You will work across ML modeling, retrieval and LLM systems, statistical methods, simulation, data and training pipelines, backend services, and user- and agent-facing product experiences. The hard part is not merely producing a plausible answer.

• Set and execute the technical roadmap for Generative Insights and Predictive Experimentation, from early prototypes through production adoption.
• Build cross-experiment learning systems that retrieve and synthesize historical experiments, detect recurring effects and segment behavior, reanalyze prior results when data or…
• Develop predictive models and simulation workflows, including simulation-based evaluation approaches, to estimate likely impact, affected segments, regression risk, and…
• Create high-quality datasets and feature or retrieval pipelines from exposures, events, metrics, experiment metadata, and replay data, with strong lineage, freshness, privacy…
• Establish rigorous evaluation through offline benchmarks, backtests, calibration, drift monitoring, prediction-to-outcome comparisons, and explicit failure or abstention behavior.

Tech stack

• Python