Staff ML Engineer, Ads Retrieval Leader

Reddit

United States

Remote

USD 230,000 - 322,000

Full time

14 days+

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Benefits offered by this job

100% remote opportunity
Comprehensive Healthcare Benefits and
401k with Employer Match
Global Benefit programs
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid VolunteerTime
Generous Paid Parental Leave

Job summary

Reddit is hiring a Staff Machine Learning Engineer for the Ads Retrieval ML team to lead retrieval modeling and end-to-end product impact at scale. You will guide data design, model development, evaluation, and deployment while mentoring engineers and shaping long-term technical direction.

You will work with large-scale data, build advanced candidate-generation and retrieval systems, and collaborate with product and ads teams to improve advertiser outcomes and user experience.

Qualifications

  • 7+ years of industry experience building and shipping applied ML products.
  • Deep experience with information retrieval, candidate generation, recommender systems, or ranking.
  • Strong understanding of retrieval modeling concepts, including DNNs, embeddings, two-tower/dual-encoder models, and ANN search.
  • Experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.

Responsibilities

  • Define the technical direction and multi-year roadmap for ads retrieval modeling.
  • Design, develop, and launch candidate-generation and retrieval models for campaigns and ads.
  • Apply modern approaches like two-tower architectures, embeddings, and sequence models to create product value.

Skills

Information retrieval
Recommender systems
Deep learning
TensorFlow
PyTorch
Production code
Experimentation
Communication

Tools

TensorFlow
PyTorch
NN search
Airflow

Job description

Reddit is hiring a Staff Machine Learning Engineer for the Ads Retrieval ML team to lead retrieval modeling and end-to-end product impact at scale. You will guide data design, model development, evaluation, and deployment while mentoring engineers and shaping long-term technical direction.

You will work with large-scale data, build advanced candidate-generation and retrieval systems, and collaborate with product and ads teams to improve advertiser outcomes and user experience.

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