Machine Learning Manager, Feed Ecosystems

Responsibilities

• 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.
• Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.
• Work closely with product, design, data science, safety, community, ads, and platform partners to identify opportunities, set expectations, and communicate your team’s work.
• Oversee the design, development, and optimization of ML systems that improve cold-start relevance, new post and community distribution, community discovery, and feed quality.
• 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.
• Collaborate with platform and infrastructure teams to build scalable AI-powered systems that support discovery, personalization, and healthy content distribution across Reddit.
• Maintain high standards for system performance, reliability, efficiency, and responsible AI practices in alignment with user needs and ecosystem health.
• 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 building and managing high-performing ML or recommender-systems teams.
• Hands-on experience with large-scale production ML systems, ideally including 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 across ambiguous problem spaces, balancing user relevance, community growth, content quality, safety, and business impact.
• Passion for developing scalable, well-designed, and responsible AI systems that improve user value while supporting a healthy and sustainable content ecosystem.
• 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.

Nice-to-Haves

• Experience with recommender systems, personalization, cold-start modeling, content understanding, or LLM-powered recommendation applications.

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