Senior Machine Learning Engineer, Ads Experimentation & Measurements

About the role

Unity's Ads Experimentation Platform team is looking for a senior machine learning engineer to lead the evolution of how we validate and optimize our global advertising ecosystem. At Unity, our ads reach billions of devices, and the ability to rapidly iterate on machine learning models or ads delivery pipelines is critical to our growth. In this role, you will be the technical authority for our experimentation and evaluation roadmap. You will bridge the gap between advanced statistical methodology and large-scale engineering, building the tools that allow ML teams to iterate faster and with higher confidence. You will join a team focused on high-velocity innovation, moving beyond standard A/B testing into the next generation of causal inference and high-sensitivity evaluation methodologies.

Responsibilities

• Product Analytics & Insights: Demonstrated ability to drive product decisions through analytics - defining metrics, building measurement frameworks, analyzing A/B test results, and translating experiment outcomes into clear, actionable insights for ML, Product, and Business partners
• Define Long-Term Value (LTV) Proxy Metrics: Research and validate surrogate metrics that correlate highly with long-term user retention, churn, and value. You will provide ML teams with short-term signals that accurately predict long-term impact, enabling faster optimization for long-term growth.
• Drive Automated ML Experimentation: Build the statistical foundations for automated pipelines that autonomously test and select optimal features and hyperparameters. This reduces manual engineering overhead and accelerates the deployment of high-performing models at scale.
• Cross-Functional Technical Leadership: Serve as the lead subject matter expert on experimentation for ML, Product, and Engineering teams. You will ensure statistical rigor is integrated throughout the product lifecycle, from initial model training to live production auctions.

Requirements

• 5+ years of experience in Data Science or Applied Research, specifically within Ad Tech, Marketplaces, or high-scale experimentation platforms.
• Advanced Education: An MS or PhD in a quantitative field (Statistics, Economics, Computer Science, Operations Research, or equivalent).
• Deep expertise in causal inference, experimental design, and frequentist/Bayesian statistics, with a proven track record of applying these to high-volume, real-time data.
• Strong programming skills in Python or Scala, and experience with large-scale data processing frameworks like Spark, Snowflake, or BigQuery.
• Practical experience implementing advanced testing methodologies like CUPED, interleaving, or switchback testing in production environments.
• Ability to translate complex statistical concepts into clear product roadmaps and mentor engineering teams on experimental rigor.
• You might also have
• Experience building or maintaining internal experimentation platforms at a major tech company.
• Familiarity with the unique challenges of long-term value (LTV) prediction and surrogate metric design in mobile gaming or digital advertising.
• Experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security
• Additional information
• Relocation support is not available for this position

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