Hinge

Lead Product Manager, Recommendations

Mid-Level
Full-Time
New York
Product

About 

Hinge

Hinge is the dating app designed to be deleted

Your Responsibilities

  • Define the product strategy. Set the long-term vision for recommendations, secure executive alignment, and bring clarity to a space that touches nearly every team and user.
  • Own the roadmap. Translate strategy into a clear, focused roadmap. Prioritize the most important work, make smart tradeoffs, and keep partners aligned as priorities evolve.
  • Communicate with clarity and influence. Own the narrative around plans, priorities, and decisions, whether you’re reviewing tradeoffs with an engineer or presenting next steps to executive leadership.
  • Develop features that shape dating. Own and evolve how we model, rank, and personalize recommendations. Lead your team through the full product development cycle, from research to concept to experiment to launch. Partner with UI-focused product and design teams to build a discovery experience that feels useful, personal, and emotionally intuitive.
  • Make decisions grounded in insight. Use experiments, behavioral data, and research to guide decisions, while navigating ambiguity and imperfect signals. Partner with data science and research to understand how the system is performing and where to focus next.
  • Collaborate across Hinge. Work with Growth, Trust & Safety, Marketing, and other teams to make sure recommendations feel integrated and aligned with the broader product experience.
  • Champion fairness and integrity. Recommendations shape visibility and connection. Ensure the system reflects Hinge’s values, avoids unintended bias, and supports an experience that feels safe and equitable for everyone.

Required Skills and Experience

  • 6+ years of product management experience, ideally on personalization, recommendations, or other ML-powered consumer products
  • Technical background or deep familiarity with the nuts and bolts of machine learning and AI
  • A track record of building and improving consumer products at scale
  • Experience partnering with engineering, data science, and research
  • Strong communication skills, especially when translating complex ideas to non-technical audiences
  • Comfort with ambiguity and making principled calls in high-impact spaces
  • Curiosity about dating and the human side of product development
  • An interest in the fairness, ethics, and inclusivity of algorithmic systems

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