Machine Learning Manager (Feed Relevance, Retrieval)

Role Overview

Join Reddit as a Machine Learning Manager to lead the Feed Retrieval team. You will set the technical vision and long-term roadmap for retrieval, oversee the design and development of retrieval systems, and work closely with cross-functional partners to ensure strong performance, reliability, and measurable impact.

Key Missions

• Define the technical vision and long-term strategy for Feed Retrieval, aligning large-scale recommendation system investments with Reddit’s product and business goals.
• Translate Feed Relevance objectives into an execution roadmap, clarifying prioritization trade-offs across:
  • model quality
  • inventory expansion
  • experimentation speed
  • infrastructure cost
  • operational reliability
• Lead the design, development, and optimization of retrieval systems that produce relevant, diverse, fresh, high-quality candidates for personalized feed experiences.

Responsibilities

• Own technical strategy, roadmap, and system quality standards for Feed Retrieval.
• Establish strong measurement and experimentation practices.
• Maintain high standards for system performance and reliability.
• Coach and grow the team; support development of ML engineers and managers.

Requirements

• Impact-driven mindset and passion for scalable, well-designed, responsible AI.
• 2+ years experience leading and managing ML or recommender-systems teams.
• Ability to develop and communicate a clear technical strategy in ambiguous problem spaces.
• Deep domain knowledge in recommender systems, especially:
  • candidate retrieval
  • embedding/indexing systems
  • ranking handoffs
  • feed personalization
  • exploration
  • content quality
  • measurement strategies
• Strong communication and collaboration skills with cross-functional partners.
• Hands-on experience with large-scale production ML systems, ideally including one or more of:
  • retrieval models
  • embedding-based systems
  • sequence models
  • transformer architectures
  • LLM-powered recommendation

Nice-to-Haves

• Experience spanning a broad mix of retrieval + ranking handoffs and production measurement/experimentation.
• Prior leadership in high-relevance, feed personalization contexts.