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Staff Machine Learning Engineer (App Ads Modeling)

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Onsite

Staff Machine Learning Engineer (App Ads Modeling)

Reddit

Staff Machine Learning Engineer (App Ads Modeling)

Skills

Deep LearningPyTorchTensorFlowMachine Learning

13 days ago

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Important information


Contract type:

Permanent

Salary:

$230,000 – $322,000 / year

Location:

United States

Work mode:

Onsite

Published on:

7 October 2026

What they need


  • We’re looking for a Staff-level Machine Learning Engineer to join Reddit’s Ads Ranking Org. This role is part of a broader effort to enhance Reddit’s ML-powered ad ranking systems through improved model architectures, contextual embeddings, and conversion-optimized modeling
  • This position will sit on the App Ads Modeling team and report directly into the Ranking Org
  • Design and train advanced ML models (e.g., DNNs, transformers) to power Reddit Ads Ranking
  • Develop and optimize features including embeddings, contextual signals, and cross-session behavior
  • Work closely with product, infra, and data teams to drive end-to-end model deployment and performance analysis
  • Mentor other MLEs and contribute to modeling best practices across the org
  • Shape the long-term modeling vision across one or more domains (conversion, app ads, shopping, brand, etc.)

Benefits

  • Comprehensive health benefits
  • Flexible vacation & Reddit global days off
  • Family planning funds & 4+ months paid parental leave
  • Personal & professional development funds
  • Paid volunteer time off
  • Workspace & home office benefits- The ideal candidate will bring strong end-to-end modeling expertise, a deep understanding of modern deep learning techniques, and a passion for building systems that drive measurable impact in ads marketplaces
  • While ads experience is a plus, strong modelers from recommendation systems, search relevance, or other performance-driven domains are encouraged to apply
  • Knowledge about Recsys or Ads funnel
  • 7+ years of industry experience, including several years in applied ML roles
  • Strong experience with Deep Learning architectures and ML frameworks (TensorFlow, PyTorch)
  • State of the Art models for Ads or Recsys experience (ex: Transformers, Recsys)
  • Experience working with large-scale datasets and complex feature pipelines
  • Comfort collaborating with infra and data teams on feature serving and training pipelines
  • Strong background in recommendation systems, ads ranking, or similar domains
  • Track record of delivering high-impact models in production settings
  • Strong problem-solving and experimentation skills
  • Experience in ads marketplaces at peer companies
  • Publications, patents, or industry contributions in applied ML or ranking systems
  • Experience with conversion modeling, app ads, or performance/brand ads

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