Develop, deploy, and grow with Unity, the world’s leading 3D game engine. Build for all major platforms from mobile, to PC and console as well as XR, acquire players, monetize your game, and power industrial applications. Backed by Sequoia.
About the role
Unity is building next-generation intelligence systems for gaming: systems that help AI-native teams understand the market and get the most out of the frontier models.
What they're looking for
- Experience in machine learning with a track record of owning production ML systems end to end, from data to serving to measured business outcome
- Deep experience in performance marketing or ad-tech modeling: predicting acquisition cost, lifetime value, return on ad spend, retention or comparable outcomes
- Strong grounding in probabilistic prediction and calibration: quantile or interval prediction, coverage, bias correction and backtesting of forecasts
- Experience building LLM-based agent systems in production: orchestration, evaluation harnesses, prompt and model versioning, and cost control
- Strong Python and modern ML tooling, plus solid data systems fundamentals across a relational store, a columnar analytics store and an event stream
- Proven ability to drive technical direction across teams, mentor senior engineers, and influence decisions without formal authority
More about this role
Unity is building next-generation intelligence systems for gaming: systems that help AI-native teams understand the market and get the most out of the frontier models.
We are hiring a Staff Machine Learning Engineer to lead this effort. You will own the end-to-end architecture, build pipelines, systems, and models, and scale a cross-disciplinary team of engine developers, game developers, and machine learning engineers. The work spans market forecasting, outcome prediction, multimodal content understanding, evaluation, and agentic systems.
Technical leadership
- Set the technical vision and architecture for our ML platform, from data ingestion, semantic layer and feature stores through model registry, evaluation and serving.
- Make the calls that keep every model output reproducible and auditable: versioned data snapshots, model and prompt versions, and cost tracked per decision.
- Define, lead, and spearhead engineering practices for the agentic era, including agentic development workflows and evaluation methodologies.
- Mentor engineers from different backgrounds.
- Partner with different functional teams and disciplines to translate expert human judgment into training signals....
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