Senior/Machine Learning Engineer — Performance Optimization

Role: Hybrid in Redwood City, CA. Must have: 3+ years of solid experience building machine learning, data science, ranking, prediction, recommendation, optimization, or large-scale data systems PubMatic is the leading AI-powered ad tech company delivering measurable advertising performance through an intelligent, unified platform that connects buyers, publishers, data partners, and commerce media across CTV, mobile app, and omnichannel environments. About the Role: We are looking for a Machine Learning Engineer to help build and improve performance optimization models for PubMatic’s Activate platform. This role is focused on applying machine learning, data analysis, feature engineering, model training, experimentation, and production ML techniques to improve advertiser outcomes across performance advertising goals such as CTR, VCR, CPC, CPA, and ROAS. The ideal candidate has strong ML fundamentals, good engineering skills, and interest in building models that operate at large scale in real production systems. What You'll Do: Build, train, evaluate, and improve machine learning models for prediction, ranking, campaign optimization, bidding, forecasting, and calibration. Work with large-scale datasets from auctions, impressions, clicks, video events, conversions, users, context, inventory, campaigns, and marketplace feedback. Develop and improve features, training datasets, labels, and evaluation workflows for performance advertising models. Analyze model performance across offline metrics, online experiments, campaign outcomes, and business KPIs. Help improve models for CTR, CVR, VCR, CPA, ROAS, app-install, user-value, and campaign-performance optimization. Work with senior ML engineers to improve calibration, model monitoring, experimentation, and production feedback loops. Debug model-quality issues related to feature quality, label quality, sparse conversions, attribution noise, delayed feedback, data freshness, or online/offline metric mismatch. Collaborate with performance advertising signal engineers to use model-ready features, labels, attribution windows, and feedback loops effectively. Partner with engineering teams to deploy models into production deci sioning systems and monitor their impact. Work cross-functionally with product, analytics, platform, and business teams to understand campaign performance problems and translate them into ML work We’d Love for You to Have 3+ years of experience building machine learning, data science, ranking, prediction, recommendation, optimization, or large-scale data systems.