Seeking a Senior Performance Advertising Engineer to optimize buyer-side and performance marketing systems. Responsibilities include designing algorithms, building data systems, and refining optimization loops to drive Return on Ad Spend (ROAS). Own technical architecture and scale data pipelines for attribution data across Mobile App (including SKAdNetwork and Privacy Sandbox), Video, Connected TV (CTV), and Desktop. Develop real-time bidding algorithms, pacing controls, and predictive models. Design scalable streaming and batch data pipelines for multi-touch attribution datasets. Improve performance across Mobile, CTV & Video, and Desktop programmatic formats. Audit data ingestion for flaws and latencies. Write high-performance, low-latency code in Python, Go, Java, or C++. Requirements: Bachelor’s or higher in quantitative field, 5+ years software engineering in performance advertising or programmatic bidding, expertise in multi-touch attribution, experience with large-scale data pipelines using Apache Spark, Flink, Kafka, Snowflake, BigQuery, and familiarity with Mobile App, CTV, and Desktop technical specs. Preferred: knowledge of OpenRTB, DSP/SSP mechanics, supply-path optimization, and production ML frameworks for CTR/CVR prediction. Location: Hybrid or remote from New York or Redwood City.
What you'll do
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Develop, benchmark, and deploy real-time bidding (RTB) algorithms, pacing controls, and predictive models to maximize ROAS and conversion tracking across CTV, Mobile App, Video, and Desktop
Design, evaluate, and implement scalable, low-latency streaming and batch data pipelines for complex conversion and multi-touch attribution datasets
Advance performance capabilities across programmatic formats: Mobile (SKAdNetwork, Attribution API, Android Privacy Sandbox), CTV & Video (cross-device graph integrations, household-level frequency capping, server-to-server attribution), Desktop (alternative identity framework integrations like UID2, LiveRamp ATS)
Audit existing data ingestion points for architectural flaws, data loss, or systemic latencies affecting attribution accuracy and campaign performance
Write high-performance, low-latency, memory-efficient code in Python, Go, Java, or C++ for ultra-scaled backend processing trillions of monthly events
Requirements
Bachelor’s, Master’s, or equivalent practical experience in Computer Science, Data Science, Statistics, Mathematics, Physics, or an analytically grounded quantitative field
5+ years of software engineering experience focusing on performance advertising, programmatic bidding, or large-scale user-conversion optimization loops
Demonstrated track record of evaluating and implementing multi-touch attribution (MTA), last-touch attribution (LTA), or incrementality testing frameworks in a production environment
Hands-on experience engineering pipelines handling terabyte-to-petabyte scale data via distributed frameworks such as Apache Spark, Apache Flink, Kafka, and cloud data warehouses (e.g., Snowflake, BigQuery)
Strong technical familiarity with technical specs supporting Mobile App (IDFA/GAID loss mitigations), CTV (App Transport Security, IFA standards), and Desktop environments
Paid leave programsPaid holidaysHealthcare insuranceDental insuranceVision insuranceDisability insuranceLife insuranceCommuter benefitsPhysical and financial wellness programsUnlimited DTO in the USReimbursement for mobileFully stocked pantriesIn-office catered lunches 5 days a week
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