Machine Learning Manager, Feed Relevance (retrieval)

Reddit Reddit · Consumer · United States · Remote · Machine Learning

Engineering Manager for Reddit's Feed Retrieval team, responsible for leading ML Engineers in building and optimizing systems that identify, retrieve, and shape content for personalized feeds. The role involves defining technical strategy, managing the team's roadmap, overseeing system development, and collaborating with cross-functional teams to build scalable, low-latency AI-powered recommendation systems.

What you'd actually do

  1. 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.
  2. 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.
  3. Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.
  4. 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.
  5. Measurement & Learning: Establish strong measurement, experimentation, and debugging practices so the team can understand retrieval quality, candidate coverage, source incrementality, and downstream impact.

Skills

Required

  • Experience Leading ML Teams: 2+ years of experience building and managing high-performing ML or recommender-systems teams.
  • Deep ML Expertise: 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.
  • Technical Domain Knowledge: Strong understanding of recommender systems, especially candidate retrieval, embedding/indexing systems, ranking handoffs, feed personalization, exploration, content quality, and measurement strategies.
  • Strategic Thinking: Ability to develop and communicate a clear technical strategy across ambiguous problem spaces, balancing user relevance, ecosystem health, system scalability, and business impact.
  • Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
  • Exceptional Communication & Collaboration: 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.

What the JD emphasized

  • lead our Feed Retrieval team
  • lead a high-impact team of Machine Learning Engineers
  • building the systems that identify, retrieve, and shape the candidate inventory powering Reddit’s personalized feeds
  • building scalable ML systems
  • 2+ years of experience building and managing high-performing ML or recommender-systems teams
  • Hands-on experience with large-scale production ML systems
  • Strong understanding of recommender systems
  • next generation of AI-powered recommendations

Other signals

  • building the systems that identify, retrieve, and shape the candidate inventory powering Reddit’s personalized feeds
  • improving personalization and discovery for users
  • building scalable ML systems that directly shape the experiences of over 120M+ daily users
  • Define the technical vision and long-term roadmap for Feed Retrieval
  • Oversee the design, development, and optimization of retrieval systems
  • 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.