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Staff Machine Learning Engineer (App Ads Modeling)

Reddit

Skills

Required

  • Recsys / Ads
  • ML
  • recommendation systems
  • ranking systems
  • applied ML
  • Deep Learning architectures
  • ads ranking
  • TensorFlow
  • PyTorch
  • Transformers
  • large-scale datasets
  • feature pipelines

Preferred

  • conversion modeling / app ads / performance/brand ads
  • machine learning models
  • modeling best practices
  • embeddings and contextual signals

Join Reddit's Ads Ranking Org as a Staff Machine Learning Engineer. In this role, you will design and train advanced ML models to enhance Reddit's ad ranking systems. You will work closely with product, infrastructure, and data teams to drive end-to-end model deployment and performance analysis. Additionally, you will mentor other machine learning engineers and contribute to modeling best practices across the organization. The ideal candidate will have 7+ years of industry experience, strong expertise in deep learning architectures, and a background in recommendation systems or ads ranking.

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

Responsibilities

  • Design and train advanced machine learning models to enhance Reddit's ad ranking systems.
  • Develop and optimize features, including embeddings and contextual signals, to improve model performance.
  • Mentor other machine learning engineers and contribute to modeling best practices across the organization.

Requirements

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
  • Publications, patents, or industry contributions in applied ML or ranking systems

Preferred

  • While ads experience is a plus, strong modelers from recommendation systems, search relevance, or other performance-driven domains are encouraged to apply
  • Experience in ads marketplaces at peer companies
  • Experience with conversion modeling, app ads, or performance/brand ads

Pay

USD 230,000 - 322,000

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