Drimva

Meta

Product Marketing Manager

$130K–$188K

Menlo Park, CA +2 · Manager · Full-time · Posted Jun 24, 2026

Location
Menlo Park, CA
New York, NY
San Francisco, CA
Experience
8+ years in ad-tech, strategic marketing, product management, or management consulting within the technology sector.
Education
Bachelor's Degree in Business, Marketing or Creative discipline; MBA or other relevant advanced degree is also listed.

About the job

Drives market requirements and go-to-market strategy for Meta advertiser products, using market research and cross-functional coordination to guide product development, launches, and growth.

What you'll do

  • Assess advertiser needs and market feedback, conduct quantitative and qualitative analysis, and inform product, engineering, and design teams.
  • Coordinate cross-functional product initiatives and align regional and vertical teams around consistent solutions that address market-specific needs.
  • Own go-to-market strategy, including positioning, communications, documentation, messaging, and sales and partnership team enablement.

What they ask for

  • 8+ years of experience in ad-tech, strategic marketing, product management, or management consulting within the technology sector.
  • Experience collaborating across cross-functional teams and gaining leadership support to resolve competing perspectives.
  • Analytical, data-driven decision-making and effective communication with technical, business, and external stakeholders.
  • Bachelor's Degree in Business, Marketing or Creative discipline.

Nice to have

  • MBA or other relevant advanced degree.
  • Experience coordinating global go-to-market end-to-end, including sales enablement and positioning/narrative; product marketing experience supporting launches is also cited.

Pay

$130,000/year to $188,000/year USD base salary; bonus and equity also stated, amounts unspecified.

AI focus

Integrate AI tools to optimize or redesign workflows and deliver measurable impact; continue developing AI skills (such as prompt/context engineering and agent orchestration) and apply responsible AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)