Staff Machine Learning Engineer

Join our team as a Staff Machine Learning Engineer, where you will set the technical vision and architecture for our ML platform. You will be responsible for ensuring the reproducibility and auditability of model outputs, defining and leading engineering practices, mentoring engineers, and partnering with different functional teams. You will build predictors of commercial outcomes, forecasting models, and design online experimentation. Additionally, you will own the feedback loop that scores predictions against realized outcomes and make the system report its own error in plain language.

- Set the technical vision and architecture for the ML platform, ensuring reproducibility and auditability of model outputs. - Define, lead, and spearhead engineering practices for agentic development workflows and evaluation methodologies. - Build predictors of commercial outcomes and forecasting models over market signals, delivering predictions as calibrated ranges.

- Experience in machine learning with a track record of owning production ML systems end to end, from data to serving to measured business outcome - Comfort building in a zero-to-one environment - Deep experience in performance marketing or ad-tech modeling: predicting acquisition cost, lifetime value, return on ad spend, retention or comparable outcomes - Proven ability to drive technical direction across teams, mentor senior engineers, and influence decisions without formal authority - Strong Python and modern ML tooling, plus solid data systems fundamentals across a relational store, a columnar analytics store and an event stream - Experience building LLM-based agent systems in production: orchestration, evaluation harnesses, prompt and model versioning, and cost control - Strong grounding in probabilistic prediction and calibration: quantile or interval prediction, coverage, bias correction and backtesting of forecasts - Experience in mobile game user acquisition, LiveOps or monetization, on the studio or publisher side - Experience with Unity or another game engine, or with automated and bot-driven playtesting - Time-series and demand forecasting experience over noisy, multi-source market signals - Experience with the Claude Agent SDK, Codex or similar frameworks for multi-agent software production - Publications or open-source contributions in forecasting, causal inference, calibration or agentic systems - Hands-on experience with BigQuery, ClickHouse, Kafka, Postgres, pgvector or their equivalents