Machine Learning Manager, Feed Relevance – Retrieval

Reddit, Inc.

Engineering Manager leading a team building systems for Reddit’s personalized feeds. Overseeing machine learning projects to enhance user experience for 120M+ daily users.

Posted 7/29/2026full-timeRemote • 🇺🇸 United StatesJuniorMid-Level💰 $253,300 - $354,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing high-performing machine learning teams, with a strong focus on developing scalable recommender systems and retrieval models. Capable of translating complex technical strategies into actionable roadmaps while fostering collaboration across cross-functional teams.

Highest-signal resume keywords

Machine Learning Team ManagementRecommender Systems DevelopmentRetrieval Model OptimizationTechnical Strategy CommunicationInterpersonal Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Large-Scale Production ML SystemsRecommender SystemsRetrieval ModelsEmbedding-Based SystemsTransformer-Based ArchitecturesLLM-Powered Recommendation ApplicationsCandidate RetrievalRanking HandoffsFeed PersonalizationMeasurement Strategies

Soft Skills

Collaborative MindsetEffective Communication

Industry Keywords

AI SolutionsSystem PerformanceOperational ReliabilityExperimentation PracticesCross-Functional Collaboration

About the role

Key responsibilities & impact

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.
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.
Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact.
Oversee the design, development, and optimization of retrieval systems that source relevant, diverse, fresh, and high-quality candidates for personalized feed experiences.
Establish strong measurement, experimentation, and debugging practices so the team can understand retrieval quality, candidate coverage, source incrementality, and downstream impact.
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.
Maintain high standards for system performance, reliability, latency, cost efficiency, and responsible recommendation practices.
Work with cross-functional partners from across the company to identify key areas of opportunity, set expectations, and communicate your team’s work.
Partner with our incredible recruiting team to attract, interview, and hire diverse and talented machine learning engineers, growing a world-class team.

Requirements

What you’ll need

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, retrieval models, embedding-based systems, sequence models, transformer-based architectures, or LLM-powered recommendation applications.
Strong understanding of recommender systems, especially candidate retrieval, embedding/indexing systems, ranking handoffs, feed personalization, exploration, content quality, and measurement strategies.
Ability to develop and communicate a clear technical strategy across ambiguous problem spaces, balancing user relevance, ecosystem health, system scalability, and business impact.
Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
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.

Benefits

Comp & perks

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