Principal Product Manager- Ads Optimization

LinkedIn•Sunnyvale, CA

1d•Hybrid

About The Position

LinkedIn is hiring a Principal Product Manager to lead the strategy and execution for LinkedIn’s Ads Quality systems and user experiences. The role defines how LinkedIn delivers ads that are relevant and valuable to members while driving strong outcomes for advertisers and the business. It spans the ads stack and involves balancing advertiser ROI, member experience, and revenue while advancing relevance, safety, and performance at scale. The position is based in Sunnyvale or San Francisco and follows a hybrid work arrangement, with work performed both from home and from a LinkedIn office on select days as determined by team business needs.

Requirements

Bachelor of Science degree in a technology-related field or equivalent experience.
At least 7 years of experience in product management or an equivalent role.

Nice To Haves

At least 5 years in product management with deep experience in trust and safety, policy, and privacy for ads.
Track record of improving advertiser ROI while maintaining member-first experiences.
Proven leadership owning business-critical roadmaps and shipping large-scale systems with measurable impact.
Strong analytical skills, including metrics design, causal inference fundamentals, experimentation, and data-driven decision-making.
Experience building B2B products and driving product planning, development, and launch.
Familiarity with ads buying technology from LinkedIn and other companies, such as Meta and Google.
Excellent cross-functional leadership and communication skills with senior stakeholders.
Suggested skills: advertising product, advertising technology integrations, analytical skills/data science, optimization, ABM, and data analysis.

Responsibilities

Define the vision, strategy, and roadmap for Ads Quality across relevance, delivery, safety, and user experience.
Set success metrics, including member impact, advertiser ROI, quality scores, and revenue lift, and drive measurable outcomes.
Partner with Data Science, Applied AI/ML, and Engineering to improve ranking models, bidding algorithms, auction signals, and creative quality at scale.
Establish rigorous experimentation frameworks, including A/B tests, holdouts, and offline evaluations, to validate causal impact.
Design end-to-end product experiences that improve perceived quality through better ad formats, controls, feedback loops, and transparency.
Influence company-level decisions through clear narratives, trade-off analyses, and executive communication.
Mentor product managers and elevate product standards and operational excellence across Ads.