Senior Principal Machine Learning Engineer - Optimization
Core
Building large-scale prediction and optimization systems for performance advertising to improve campaign outcomes (CTR, VCR, CPC, CPA, ROAS) and evolve the platform into a performance optimization engine.
Role type
Senior Principal Machine Learning Engineer (Optimization)
Builds
Real-time decisioning systems for bidding, pacing, ranking, and value estimation in programmatic advertising.
Domain
Digital Advertising / Machine Learning / Optimization
Deliverable
production ML models
Required skills
Large-scale prediction and optimization system design, supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, model monitoring, distributed ML workflows, Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost
Preferred skills
Ads, search, recommendations, marketplaces, e-commerce, fintech, pricing, bidding, real-time optimization, exploration/exploitation, counterfactual evaluation, uplift modeling, delayed-feedback modeling, model observability, A/B testing, incrementality testing
Technologies
Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost
Responsibilities
Build and improve ML models for campaign optimization, prediction, ranking, bidding, forecasting, and calibration; Develop algorithms balancing spend delivery, cost efficiency, and marketplace dynamics; Partner with signal engineers to define features, labels, and training datasets; Partner with engineering and product teams to translate model outputs into real-time decisioning systems; Provide technical leadership and mentorship to engineers and applied scientists.
Seniority
Senior, hands-on IC with technical leadership
