Senior Product Manager - AI​/ML

The Role

We are looking for a Senior Product Manager to own search relevance, data architecture, and the data pipelines that power the next generation of native search ads across ad Marketplace's publisher and AI Chat surfaces. This is a high-leverage, hands‑on role with executive visibility. You will sit at the intersection of Product, AI/ML, Supply, Product Analytics, and Supply Analytics, and you will be responsible for how we turn query understanding, feed quality, and relevance signals into measurable lift for consumers, publishers, and advertisers.

You will help define what native search advertising looks like on AI surfaces. The work ranges from scoping the data platforms and feature stores that feed our models, to prototyping ranking and query‑understanding ideas, to shipping them through a tight partnership with engineering and data science.

• Own the product area. Own the roadmap for search relevance, data architecture, and data pipelines across native search and AI Chat surfaces, from ideation through launch and iteration.

• Shape the data and ML foundation. Define, prioritize, and scope the data, feature, and feed investments that drive retrieval, ranking, and query understanding across the stack.

• Lead on AI surfaces. Drive the product strategy for ad Marketplace's native ad presence on AI Chat surfaces, extending our first‑to‑market, first‑to‑scale position into durable advantage.

• Prototype and technically scope. Write PRDs, build lightweight prototypes, and run technical scoping with ML engineers, data scientists, and data platform partners. You will be expected to read a schema, sketch a pipeline, and pressure test a model evaluation plan.

• Partner across the org. Work directly with Product Analytics, Supply Analytics, AI/ML, and Supply to align on metrics, experimentation strategy, and the trade‑offs between relevance, yield, and publisher health.

• Measure what matters. Define the metrics and evaluation frameworks that tell us when relevance is actually getting better, not just when a model is shipping.

• Bring clarity. Translate ambiguous, cross‑team problems into clear product plans, sequenced investments, and decisions the executive team can act on.

• 5 to 8 years of product management experience, including at least 3 to 4 years in ad tech.

• Proven track record building data, ML, or AI products end to end. You have shipped something real that depended on data pipelines, feature engineering, or model output, and you can speak to the trade‑offs you made.

• High technical literacy with hands‑on prototyping and technical scoping experience. Comfort reading SQL, exploring data, sketching pipelines, and working through model evaluation plans with ML and data science partners.

• Working fluency in the publisher and SSP ecosystem, including supply‑side workflows, integrations, feed quality, and marketplace dynamics.

• Strong product instincts for search and relevance: retrieval, ranking, query understanding, evaluation, and the experimentation methods that actually surface causal lift.

• Excellent written communication. You can take a tangled, cross‑team problem and make it legible to an executive in one page.

• Comfort operating with autonomy in fast‑moving, ambiguous environments, with the grit to drive decisions when data is incomplete.

• Direct experience with AI Chat, generative search, or LLM‑powered surfaces, especially monetization, ranking, or retrieval for those surfaces.

• Experience working with or integrating against DSPs, SSPs, identity providers, or product feed / catalog systems.

• Background in data platform or feature store product work.

• Hands‑on experience with experimentation platforms, offline evaluation, and online A/B testing at scale.

Compensation Range: $170,000 to $210,000, plus equity and bonus.

This range represents the low and high end of the base salary someone in this role may earn as an employee of ad Marketplace in the New York office. Salaries will vary based on various factors including but not limited to professional and academic experience; training; associated responsibilities; and other business and organizational needs. The range listed is just one component of our total compensation package for employees.

Salary decisions are dependent on the circumstances of each hire.