Senior Principal Machine Learning Engineer – Optimization

PubMatic

Senior Principal Machine Learning Engineer focused on building high-scale optimization capabilities for PubMatic’s Activate platform. Applying ML techniques to improve campaign performance in a hybrid role based in Redwood City, CA.

Posted 6/24/2026full-timeRedwood City • California • 🇺🇸 United StatesSenior💰 $260,000 - $330,000 per yearWebsite

Tech Stack

Tools & technologies

JavaPythonPyTorchSparkSQLTensorflow

About the role

Key responsibilities & impact

Build and improve machine learning models for campaign optimization, prediction, ranking, bidding, forecasting, and calibration.
Develop models and algorithms that improve advertiser outcomes while balancing spend delivery, cost efficiency, campaign goals, marketplace dynamics, and system constraints.
Work on large-scale ML systems using signals from auctions, impressions, clicks, video events, conversions, users, context, inventory, campaigns, and marketplace feedback.
Design and improve CTR, CVR, VCR, CPA, ROAS, app-install, user-value, and campaign-performance models.
Develop bidding, pacing-aware optimization, ranking, exploration, and value-estimation approaches for performance advertising.
Improve model calibration, online/offline evaluation, experimentation, observability, and production feedback loops.
Reason through sparse conversions, delayed feedback, biased logs, cold-start campaigns, attribution noise, and online/offline metric mismatch.
Partner with performance advertising signal engineers to define model-ready features, labels, attribution windows, negative examples, training datasets, and online serving requirements.
Partner with engineering, product, analytics, and platform teams to translate model outputs into real-time decisioning systems.
Help evolve Activate from a media buying execution platform into a performance optimization platform.
Provide technical leadership and mentorship to engineers and applied scientists working on performance optimization problems.

Requirements

What you’ll need

10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
Experience building large-scale prediction or optimization systems in production.
Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
Experience working with large-scale data and distributed ML workflows.
Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
Ability to provide technical leadership across ambiguous, high-impact optimization problems.
BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Benefits

Comp & perks

Paid leave programs
Paid holidays
Healthcare, dental and vision insurance
Disability and life insurance
Commuter benefits
Physical and financial wellness programs
Unlimited DTO in the US (that we actually require you to use!)
Reimbursement for mobile
Fully stocked pantries plus in-office catered lunches 5 days per week.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningrankingpredictionoptimizationbiddingcalibrationsupervised learningstatistical evaluationmodel monitoringconversion modeling

Soft Skills

technical leadershipmentorshipreasoningproblem-solvingcollaboration

Certifications

BS in Computer ScienceMS in Computer SciencePhD in Computer ScienceBS in Machine LearningMS in Machine LearningPhD in Machine LearningBS in StatisticsMS in StatisticsPhD in StatisticsBS in Mathematics