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Principal Product Manager AI Content Understanding & Feed Relevance

LinkedIn


Job Location:

Sunnyvale, CA - USA

Monthly Salary: Not provided by the employer
Posted: 24 October 2026 (4 hours ago)
Application Deadline: 21 January 2027
Vacancies: 1 Vacancy

Job Summary

This role will be based in Mountain View or San Francisco.

At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team.

At LinkedIn our mission is to connect the worlds professionals to make them more productive and successful. The Feed team sits at the heart of that mission helping members discover ideas connect and find opportunity. As a Principal Product Manager on the Feed Relevance team youll shape how cutting-edge machine learning and foundation models connect hundreds of millions of professionals to what matters most helping define the future of relevance trust and engagement on LinkedIn.

Were looking for a Principal Product Manager to lead the next generation of AI-powered content understanding and quality systems that shape the LinkedIn Feed. This is a senior individual contributor role for a proven product leader who can define bold strategy influence across disciplines and deliver at massive scale.

In this role youll shape how we leverage machine learning large language models and foundation models to understand the content shared on LinkedIn and translate that understanding into more relevant valuable and trustworthy recommendations. Youll drive systems that identify high-quality content surface meaningful professional insights and reduce the distribution of low-quality or harmful content balancing member value engagement and long-term ecosystem health.

Youll partner deeply with AI Research Engineering Data Science and Trust & Safety teams to develop and scale content understanding capabilities that power Feed ranking and recommendations. Beyond content understanding youll have opportunities to influence the broader evolution of LinkedIns recommendation systems and deliver meaningful improvements to how millions of members discover content conversations and professional perspectives.

Responsibilities:

  • Define and execute the AI product strategy for content understanding and quality across LinkedIn Feed partnering with PMs Applied Research Engineering Data Science and Trust & Safety to deliver measurable improvements in relevance member value and ecosystem health.
  • Lead the development of large-scale ML and foundation model-powered systems that understand content topics intent quality credibility and professional value translating these insights into actionable signals for ranking and recommendation systems.
  • Drive the evolution of content quality and recommendation policies that amplify valuable authentic content while reducing low-quality misleading or harmful content balancing short-term engagement with long-term member trust and ecosystem health.
  • Translate member experience goals and business outcomes into clear model objectives evaluation frameworks and success metrics ensuring alignment between AI capabilities recommendation quality and product strategy.
  • Partner with Applied Research and Infrastructure Engineering to advance scalable content understanding capabilities including LLM-based classification content representations model evaluation and efficient inference at LinkedIn scale.
  • Lead cross-functional product development from problem definition and requirements through experimentation policy alignment model deployment and launch.
  • Use data experimentation and qualitative insights to identify opportunities evaluate model and policy performance and continuously improve content quality and Feed relevance.
  • Collaborate with Feed ranking and personalization teams to integrate content understanding signals into end-to-end recommendation systems influencing how content is retrieved ranked and distributed to members.
  • Stay ahead of advances in AI content understanding and recommendation systems identifying opportunities to leverage emerging technologies to differentiate LinkedIns Feed experience.
  • Communicate product strategy priorities tradeoffs and outcomes clearly to executive stakeholders and cross-functional partners influencing the broader direction of LinkedIns AI-powered recommendations.

Qualifications :

Basic Qualifications:

  • BS/BA degree in a technology-related field or equivalent practical experience.
  • 8 years of experience in product management or an equivalent role.

Preferred Qualifications:

  • MS degree in Computer Science Machine Learning or a related technical field.
  • 10 years of experience in product management including experience leading complex AI/ML-driven products at scale.
  • Deep understanding of machine learning ranking algorithms and recommender systems with experience building or improving large-scale Feed Search Discovery or content recommendation products.
  • Experience developing or leveraging content understanding systems including content classification semantic understanding embeddings LLMs multimodal models or content quality assessment.
  • Proven track record of delivering complex ML-driven systems end-to-end from problem definition and data strategy to model deployment evaluation experimentation and iteration.
  • Experience translating content quality trust and safety objectives into scalable product policies model capabilities and measurable improvements in member experience and ecosystem health.
  • Strong understanding of the tradeoffs between relevance engagement content quality creator incentives and long-term ecosystem health in recommendation systems.
  • Demonstrated ability to define and execute AI product strategy in close partnership with Applied Research Engineering Data Science and Infrastructure teams.
  • Experience working with large-scale AI systems including model evaluation human labeling training data quality and inference efficiency.
  • Strong expertise in experimentation A/B testing causal inference and multi-objective optimization within ranking or recommendation systems.
  • Exceptional communication and cross-functional leadership skills with the ability to simplify complex technical concepts influence senior stakeholders and drive alignment across teams.
  • Passion for building AI-powered experiences that help members discover trustworthy relevant and professionally valuable content.

Suggested Skills:

  • Applied AI/ML
  • Content Understanding & Classification
  • Content Quality & Ecosystem Health
  • Feed Ranking & Relevance
  • Recommender Systems

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $187000 to $305000. Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor. 

The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :

Equal Opportunity Statement 

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race color religion creed gender national origin age disability veteran status marital status pregnancy sex gender expression or identity sexual orientation citizenship or any other legally protected class.

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A request for an accommodation will be responded to within three business days. However non-disability related requests such as following up on an application will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about discussed or disclosed their own pay or the pay of another employee or applicant. However employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information unless the disclosure is (a) in response to a formal complaint or charge (b) in furtherance of an investigation proceeding hearing or action including an investigation conducted by LinkedIn or (c) consistent with LinkedIns legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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No


Employment Type :

Full-time


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