Instacart

Senior Product Manager, Ads Quality

Rol remoto de Product Management con fit claro de ubicación del candidato.

PublicadoAgregado recientemente

Países elegibles2 países aceptados

Señal de seniorityLead

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

CanadáEstados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

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.

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.

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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