Senior Advertising Engineer

Role:

Hybrid in Redwood City, CA, or New York, NY (Will consider Remote for the right candidate)

Must have: Experience in performance advertising, programmatic bidding, or large-scale user-conversion optimization loops

Pub Matic 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.

We are seeking a Senior Performance Advertising Engineer to own and drive the optimization of our buyer-side and performance marketing systems. In this role, you will be directly responsible for designing algorithms, building data systems, and refining optimization loops that drive Return on Ad Spend (ROAS) for our Advertisers and Agencies. You will own the technical architecture and end-to-end evaluation, implementation, and scaling of robust data pipelines for attribution data.

This position spans our complete omnichannel environment, requiring expert-level performance engine development across Mobile App (including privacy‑aware frameworks like SKAdNetwork and Privacy Sandbox), Video, Connected TV (CTV), and Desktop environments.

• ROAS Optimization & Algorithmic Design: Develop, benchmark, and deploy real‑time bidding (RTB) algorithms, pacing controls, and predictive models aimed squarely at maximizing ROAS and conversion tracking across all screens (CTV, Mobile App, Video, and Desktop).
• Attribution Data Pipelines: Design, evaluate, and implement scalable, low‑latency streaming and batch data pipelines that ingest, validate, and process complex conversion and mult‑touch attribution (MTA) datasets.
• Omnichannel Execution: Advance Pub Matic’s performance capabilities across specific programmatic formats:
  • Mobile: Build robust mechanisms that thrive within SKAdNetwork, Attribution API, and Android Privacy Sandbox constraints.
  • CTV & Video: Implement precise cross‑device graph integrations, household‑level frequency capping, and server‑to‑server attribution systems.
  • Desktop: Innovate alternative identity framework integrations (e.g., UID2, Live Ramp ATS) to sustain high attribution fidelity post‑third‑party cookies.
• Data Pipeline Evaluation: Constantly audit existing data ingestion points for architectural flaws, data loss, or systemic latencies that negatively skew attribution accuracy and campaign performance.
• Scalable Systems Engineering: Write high‑performance, low‑latency, and memory‑efficient code (Python, Go, Java, or C++) matching our ultra‑scaled backend layer that processes trillions of monthly events.

• Deep understanding of the OpenRTB protocol, DSP/SSP mechanics, and supply‑path optimization (SPO).
• Experience deploying production‑grade Machine Learning frameworks for CTR/CVR prediction.
• Strong system‑level performance benchmarking skills (profiling memory allocation, reducing I/O bottlenecks).

• Education: Bachelor’s, Master’s, or equivalent practical experience in Computer Science, Data Science, Statistics, Mathematics, Physics, or an analytically grounded quantitative field.
• Experience: 5+ years of software engineering experience focusing on performance advertising, programmatic bidding, or large‑scale user‑conversion optimization loops.
• Attribution Domain Expertise: Demonstrated track record of evaluating and implementing multi‑touch attribution (MTA), last‑touch attribution (LTA), or incrementality testing frameworks in a production environment.
• Data Engineering & Scale: 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, Big Query).
• Format Versatility: Strong technical familiarity with technical specs supporting Mobile App (IDFA/GAID loss mitigations), CTV (App Transport Security, IFA standards), and Desktop environments.

Pub Matic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize…