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Machine Learning Manager, Feed Ecosystems

AI Summary
Reddit is seeking an Engineering Manager to lead the Feed Ecosystems machine learning team. The role owns technical strategy and delivery for large-scale recommendation systems that improve personalization, cold-start relevance, community discovery, and healthy content distribution. The manager will coach ML engineers and collaborate with product, design, data science, safety, ads, platform, and community partners. Success requires strong recommender-systems expertise, responsible-AI judgment, operational rigor, and the ability to align ecosystem-quality outcomes with user and business goals.
Remote from
USA
Salary
USD 253,300–354,600 / yr
Employment
Full Time
Experience
Senior
Published
Apply before
5 Dec 2026
Listing views
16
Application actions
0
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Opportunity details

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.
  • Platform & Infrastructure Collaboration: Collaborate with platform and infrastructure teams to build scalable AI-powered systems that support discovery, personalization, and healthy content distribution across Reddit.
  • Operational Excellence: Maintain high standards for system performance, reliability, efficiency, and responsible AI practices in alignment with user needs and ecosystem health.
  • Recruiting & Growth: Partner with our recruiting team to attract, interview, and hire diverse and talented machine learning engineers, growing a world-class team.

Qualifications:

  • Experience Leading ML Teams: 2+ years of experience building and managing high-performing ML or recommender-systems teams.
  • Deep ML Expertise: Hands-on experience with large-scale production ML systems, ideally including recommender systems, personalization, cold-start modeling, content understanding, or LLM-powered recommendation applications.
  • Technical Domain Knowledge: Strong understanding of recommender systems, including candidate retrieval, ranking, value modeling, ecosystem dynamics, and measurement strategies.
  • Strategic Thinking: 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.
  • Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI systems that improve user value while supporting a healthy and sustainable content ecosystem.
  • Exceptional Communication & Collaboration: 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:

  • 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

#LI-remote, #LI-JS5

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$253,300—$354,600 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior people-management and technical-leadership role for production recommender systems operating at very large scale. It requires balancing ambiguous ecosystem goals, ML quality, safety, infrastructure constraints, and cross-functional priorities.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$303,950
US market range (per year)$240k–$380k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of $253,300–$354,600 USD. The yearly pay period is inferred from the range, US location, and senior full-time engineering-management context. Estimated US market compensation for comparable ML engineering manager roles is approximately $240,000–$380,000 per year in base salary; equity and any commission are excluded.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you define success for a feed ecosystem that must balance engagement, discovery, and community health?

I would establish a metric hierarchy that includes relevance and engagement alongside retention, contribution quality, creator or community distribution, negative-feedback signals, and safety indicators. I would use guardrails and long-term experiments to ensure local ranking gains do not harm ecosystem health.

Describe your approach to improving recommendations for logged-out or low-signal users.

I would combine contextual features, content and community embeddings, geographic or language signals where appropriate, popularity adjusted for quality, and exploration mechanisms. I would measure performance separately for low-signal cohorts and progressively personalize as reliable behavioral signals emerge.

How do you lead an ML team through an ambiguous technical roadmap?

I translate company outcomes into clear problem statements, identify the highest-leverage bets and dependencies, and define measurable milestones. I communicate trade-offs early, keep the roadmap adaptable to experiment results, and give team members ownership of well-scoped technical decisions.

What safeguards would you apply when deploying a new feed-ranking model?

I would require offline evaluation, cohort analysis, bias and safety reviews, staged rollout, online guardrail metrics, rollback plans, and ongoing monitoring for drift. I would also partner with policy and safety teams to assess predictable effects on vulnerable communities and content distribution.

How would you work with product and platform teams when model improvements require major infrastructure investment?

I would quantify expected user and business impact, clarify latency, reliability, and cost requirements, and compare incremental and platform-level options. A joint roadmap with shared milestones, ownership, and success criteria helps ensure infrastructure work supports durable product outcomes.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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