Machine Learning Manager, Feed Ecosystems

About this role

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .

Reddit is looking for an experienced Engineering Manager to lead our Feed Ecosystems team. In this role, you’ll lead a high-impact team of Machine Learning Engineers focused on building recommendation systems that support sustainable growth across users, posts, and communities. Your team will improve relevance for new, low-signal, and logged-out users; help new posts and communities find the right audiences; and develop ML systems that balance personalization, discovery, and ecosystem quality across Reddit’s 100,000+ active communities.

If applying ML / AI in production to improve Reddit Relevance and strengthen Reddit’s community ecosystem excites you, then you’ve found the right place. Responsibilities: Define Technical Vision & Strategy: 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. Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.

Cross-Functional Partnership: Work closely with product, design, data science, safety, community, ads, and platform partners to identify opportunities, set expectations, and communicate your team’s work. Technical Execution & Delivery: Oversee the design, development, and optimization of ML systems that improve cold-start relevance, new post and community distribution, community discovery, and feed quality. Quality & Ecosystem Measurement: 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.