Senior Machine Learning Manager - Ads Retrieval

3 Minutes ago • All levels

Job Summary

Job Description

As a Senior Machine Learning Manager, you will lead and grow the Ads Retrieval team, combining ML expertise with people leadership and strategic vision. You'll build retrieval solutions that scale with Reddit's growth, impacting revenue, user satisfaction, and advertiser outcomes. The role involves overseeing ML model and infrastructure development, ensuring robust end-to-end solutions, and building a high-impact team. You will collaborate with cross-functional teams and drive operational excellence by championing system reliability and model quality. This role powers relevance and performance at scale for Reddit’s Ads business, leading the team that supports large-scale ad indexing, querying, and candidate sourcing.
Must have:
  • Deep experience developing large-scale ML systems in production
  • Strong knowledge of early-stage ad ranking and embedding techniques
Good to have:
  • Familiarity with auction systems and advertiser KPIs
  • Experience with ads retrieval, targeting, and marketplace dynamics
Perks:
  • Comprehensive Health benefits
  • Retirement Savings plan with matching contributions
  • Workspace benefits for your home office
  • Personal & Professional development funds
  • Family Planning Support
  • Flexible Vacation & Reddit Global Days Off

Job Details

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 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

We’re looking for a Senior Machine Learning Manager to lead and grow the Ads Retrieval team. This person will combine deep ML technical expertise, people leadership, and strategic vision to build retrieval solutions that scale with Reddit’s growth and complexity. You’ll oversee the development of models and infrastructure that directly impact revenue, user satisfaction, and advertiser outcomes. You’ll play a foundational role in the success of Reddit’s Ads business—leading the team that powers relevance and performance at scale. This is a high-impact leadership opportunity for someone passionate about cutting-edge ML, information retrieval, and marketplace systems.

The Ads Retrieval team is responsible for identifying and sourcing the most relevant, engaging, and high-quality ads from an enormous candidate pool—often in the millions to billions. This team ensures a strong top-of-funnel supply of ad candidates for downstream ranking, balancing relevance to users and performance for advertisers. Our systems support large-scale ad indexing, querying, and candidate sourcing, and our ML models play a critical role in ensuring the most relevant ads are retrieved efficiently. Retrieval is foundational to our success in both revenue and user experience—and we’re just getting started.

 

Responsibilities:

Set Technical Vision & Strategy

  • Define and execute the roadmap for Reddit’s ads retrieval systems—balancing innovation, model performance, system scalability, and business priorities.
  • Leverage domain expertise to influence strategy across the broader Ads Engineering organization.

Oversee ML Model and System Development

  • Lead the design and development of ML models for large-scale retrieval, including deep learning, embeddings, indexing, and early-stage ranking techniques.
  • Ensure the team is delivering robust end-to-end solutions—from feature engineering and training to deployment, evaluation, and monitoring.

Build & Scale a High-Impact Team

  • Recruit, mentor, and develop a diverse and inclusive team that thrives on collaboration and ownership.
  • Promote a culture of continuous learning, experimentation, and technical excellence.

Collaborate Cross-Functionally

  • Partner closely with Product Managers, Data Scientists, Backend Engineers, and leadership across Reddit’s Ads org.
  • Translate business goals and user engagement metrics into engineering solutions and measurable outcomes.

Drive Operational Excellence

  • Champion system reliability, model quality, and code maintainability.
  • Identify opportunities to improve engineer velocity, efficiency, and impact across the ML lifecycle.

Requirements:

  • Deep experience developing large-scale ML systems in production.
  • Strong knowledge of early-stage ad ranking, embedding techniques, and candidate sourcing.
  • Familiarity with auction systems, advertiser KPIs, or ad quality measurement.

Technical & Domain Expertise

  • ML & Retrieval Systems: Deep experience applying ML to large-scale information retrieval, recommendation systems, or ad retrieval problems.
  • ML Frameworks & Lifecycle: Strong proficiency in TensorFlow or PyTorch, with a track record of managing models from development to deployment and performance monitoring.
  • Scalable Systems: Expertise building high-throughput data pipelines and indexing systems that retrieve, process, and rank candidates efficiently.
  • Ads Ecosystem: Experience with ads retrieval, targeting, and understanding marketplace dynamics is highly valued.

Leadership Attributes

  • People Management: Experience managing multiple ML teams, with a focus on mentorship, hiring, and performance management.
  • Strategic Execution: Ability to align a technical roadmap with business outcomes and drive it through to delivery.
  • Strong Communicator: Able to clearly explain complex technical concepts to cross-functional stakeholders.
  • Service Mindset: Solutions-oriented, adaptable, and deeply invested in both team and company success.

 

Benefits:

  • Comprehensive Health benefits
  • Retirement Savings plan with matching contributions
  • Workspace benefits for your home office
  • Personal & Professional development funds
  • Family Planning Support
  • Flexible Vacation & Reddit Global Days Off

#LI-Remote

 

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