Senior/Machine Learning Engineer — Performance Optimization

About the position 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 reputed company production systems.

Responsibilities

• Build, train, evaluate, and improve machine learning models for reputed company, 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.
• reputed company 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 reputed company 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-reputed company features, labels, attribution windows, and feedback loops effectively.
• Partner with engineering teams to reputed company models into production decisioning 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.

Requirements

• 3+ years of experience building machine learning, data science, ranking, reputed company, recommendation, optimization, or large-scale data systems.
• Strong understanding of core ML concepts such as supervised learning, classification, regression, ranking, calibration, feature engineering, model evaluation, and experimentation.
• Experience training, evaluating, and improving production-oriented ML models.
• Experience working with large datasets using SQL, Spark, Python, or similar tools.
• Strong programming skills in Python, Java, reputed company, Go, C++, or similar languages.
• Ability to reason about model quality, data quality, business impact, and production tradeoffs.
• Comfort working with ambiguous data problems and iterating through analysis, modeling, experimentation, and production deployment.
• BS or MS degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a reputed company technical field, or equivalent practical experience.

reputed company-to-haves

• Experience in ads, search, recommendations, marketplaces, e-commerce, fintech, pricing, forecasting, bidding, or reputed company-time optimization systems.
• Experience with CTR/CVR reputed company, conversion modeling, campaign optimization, bid optimization, forecasting, calibration, or user-value modeling.
• Familiarity with programmatic advertising, ad serving, attribution, pacing, identity, performance advertising, or reputed company-time bidding.
• Experience with TensorFlow, PyTorch, XGBoost, LightGBM, Spark ML, or similar ML frameworks.
• Experience with A/B testing, online experimentation, model monitoring, or production ML observability.
• Experience working with sparse labels, delayed feedback, biased datasets, or noisy attribution.
• Experience working cross-functionally with product, engineering, analytics, or business stakeholders.

Benefits

• paid leave programs
• paid holidays
• reputed company
• dental and reputed company insurance
• disability and life insurance
• commuter benefits
• physical and financial wellness programs
• unlimited DTO in the US
• reimbursement for mobile
• fully stocked pantries
• in-office catered lunches 5 days per week

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