Resumo da vaga

Senior Product Manager, Ads Quality

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

About the Job

  • Own the product vision and roadmap for ads quality systems, including auction mechanics, marketplace balance, and the signals that govern ad ranking and relevance across Instacart's retail media network.
  • Drive the strategy and execution for increasing the velocity of experimentation across the ads quality team — designing frameworks that allow the team to test, learn, and iterate faster without sacrificing rigor or integrity.
  • Work hands-on with machine learning engineers and ads engineers to translate complex ML model outputs and auction dynamics into clear product requirements, hypotheses, and measurable outcomes.
  • Define and track the right success metrics for ads quality, navigating tradeoffs between advertiser performance, shopper experience, and marketplace health — and communicating those tradeoffs clearly to senior stakeholders.
  • Operate in a fast-paced, constantly evolving environment where priorities shift, new data surfaces frequently, and the ability to make good decisions under uncertainty is essential to moving the business forward.

About You

  • 2+ years of product management experience in online advertising, ad tech, or a closely related domain — with a demonstrated understanding of auction mechanics, bidding systems, or ad quality signals.
  • 2+ years of experience working directly with machine learning teams or ML-driven products, with the ability to engage substantively in technical conversations about model design, evaluation, and tradeoffs.
  • Proven track record of defining and executing on product roadmaps in complex, data-rich environments with multiple cross-functional stakeholders.
  • Strong analytical skills with experience using data to inform product decisions, measure impact, and design experiments.

About You

  • Hands-on familiarity with large language models (LLMs) and how they can be applied within ads or ranking systems.
  • Experience working with ads machine learning models in a production environment, including relevance scoring, auction optimization, or quality filtering.
  • Prior experience at a retail media network, demand-side platform, or supply-side platform, with exposure to the full advertising stack.
  • Comfort operating in ambiguous, high-growth environments where structure and process are still being built — and an eagerness to help build them.
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