Machine Learning Manager, Feed Ecosystems

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

Engineering Manager to lead a Machine Learning team focused on building and optimizing recommendation systems for Reddit's feed, aiming to improve user engagement, content discovery, and community health.

What you'd actually do

  1. Define the technical vision and long-term roadmap for Feed Ecosystems, aligning recommender-system investments with Reddit’s goals around user growth, contribution, community health, and high-quality discovery.
  2. Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.
  3. Work closely with product, design, data science, safety, community, ads, and platform partners to identify opportunities, set expectations, and communicate your team’s work.
  4. Oversee the design, development, and optimization of ML systems that improve cold-start relevance, new post and community distribution, community discovery, and feed quality.
  5. Help define and operationalize signals for subjective and objective quality, ensuring Feed systems optimize not only for engagement, but also for user value, community health, contribution, and long-term ecosystem outcomes.

Skills

Required

  • Experience leading ML teams
  • Experience building and managing high-performing ML or recommender-systems teams
  • Hands-on experience with large-scale production ML systems
  • Experience with recommender systems, personalization, cold-start modeling, content understanding, or LLM-powered recommendation applications
  • Strong understanding of recommender systems, including candidate retrieval, ranking, value modeling, ecosystem dynamics, and measurement strategies
  • Ability to develop and communicate a clear, compelling technical strategy
  • Exceptional Communication & Collaboration skills
  • Interpersonal skills and a collaborative mindset

Nice to have

  • LLM-powered recommendation applications

What the JD emphasized

  • 2+ years of experience building and managing high-performing ML or recommender-systems teams
  • large-scale production ML systems
  • recommender systems

Other signals

  • building recommendation systems
  • improving relevance for users
  • developing ML systems for personalization and discovery