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Machine Learning Manager, Feed Relevance (Retrieval)

Reddit· ML & Search
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Hybrid (United States)$253.3k - $354.6kFull-timePosted 2mo ago

About the role

Engineering Manager to lead the Feed Retrieval team, building scalable ML systems that identify, retrieve, and shape candidate inventory for Reddit’s personalized feeds.

Responsibilities

  • Define Technical Vision & Strategy: Define the technical vision and long-term roadmap for Feed Retrieval, aligning large-scale recommender-system investments with Reddit’s product, ecosystem, and business objectives.
  • Roadmap & Prioritization: Translate broad Feed Relevance goals into a focused team roadmap, making clear prioritization tradeoffs across model quality, inventory expansion, experimentation velocity, infrastructure cost, and operational reliability.
  • Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.
  • Technical Execution & Delivery: Oversee the design, development, and optimization of retrieval systems that source relevant, diverse, fresh, and high-quality candidates for personalized feed experiences.
  • Measurement & Learning: Establish strong measurement, experimentation, and debugging practices so the team can understand retrieval quality, candidate coverage, source incrementality, and downstream impact.
  • Platform & Infrastructure Collaboration: Collaborate with ML platform, infrastructure, ranking, safety, and product teams to build scalable, low-latency retrieval systems that can support the next generation of AI-powered recommendations.
  • Operational Excellence: Maintain high standards for system performance, reliability, latency, cost efficiency, and responsible recommendation practices.
  • Cross-Functional Partnership: Work with cross-functional partners from across the company to identify key areas of opportunity, set expectations, and communicate your team’s work.
  • Recruiting & Growth: Partner with our recruiting team to attract, interview, and hire diverse and talented machine learning engineers, growing a world-class team.

Qualifications

  • 2+ years of experience leading ML or recommender-systems teams.
  • Hands-on experience with large-scale production ML systems, ideally including recommender systems, retrieval models, embedding-based systems, sequence models, transformer-based architectures, or LLM-powered recommendation applications.
  • Strong understanding of recommender systems, especially candidate retrieval, embedding/indexing systems, ranking handoffs, feed personalization, exploration, content quality, and measurement strategies.
  • Ability to develop and communicate a clear technical strategy across ambiguous problem spaces, balancing user relevance, ecosystem health, system scalability, and business impact.
  • Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
  • Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners.

Skills

Required:Technical leadershipLarge-scale production ML systemsRecommender systems

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave
Last updated Oct 7, 2026. Interested? Apply on the company site.
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