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Senior Machine Learning Engineer, Ads Targeting



Software Engineering
San Francisco, CA, USA
Posted on Tuesday, May 2, 2023

We’re evolving and continuing our mission to bring community, belonging, and empowerment to everyone in the world. Providing a delightful and relevant experience to our users applies to our Ads like all of our offerings, and we’re excited to build a product that is best-in-class for our users and advertisers. The year ahead is a busy one - join us!

Reddit is continuing to grow our teams with the best talent. We're completely remote-friendly and will continue to be after the pandemic.

Ads Targeting ML engineers are focused on designing and implementing end-to-end ML systems and solutions for improving targeting products. Some examples of projects that the team owns:

  • Improve targeting models’ quality by experimenting with in-house models or open-source options
  • Create deep learning encoders to create Ads Targeting specific embeddings for contextual and behavioral entities
  • Leverage large language models to create better representations for Reddit entities and content for ads targeting purposes
  • Develop highly efficient retrieval ranking and models with a good balance between model performance and computation efficiency
  • Create dense retrieval solutions by leveraging the most performant approximate nearest neighbor search

As a Senior Machine Learning Engineer in the ads targeting team, you will research, formulate and execute our mission to deliver the most relevant audiences to advertisers under the right context with data and ML-driven solutions.

Your Responsibilities:

  • Build large-scale and low-latency nearest-neighbor search systems based on dense representations/embeddings
  • Build custom deep learning models to learn representations for Reddit-specific entities and advertiser campaign entities
  • Systematic feature engineering works to convert all kinds of raw data in Reddit (dense & sparse, behavior & content, etc) into features with various FE technologies such as aggregation, embedding, sub-models, etc.
  • Be a mentor and cross-functional advocate for the team
  • Contribute meaningfully to team strategy. We give everyone a seat at the table and encourage active participation in planning for the future.

Who You Might Be:

  • Successful track record of applying machine learning techniques in addressing real-world problems
  • Comfort analyzing high-volume natural language and multimodal data from varying sources
  • Experience communicating complex research and ideas in a clear, precise, and actionable manner
  • Experience with designing end-to-end ML systems
  • Experience in content recommendations, NLP, and ads personalization
  • Experience with representation learning, deep learning, and approximate nearest neighbor search
  • Experience building nearest-neighbor search systems
  • Experience with the Ads domain is a plus
  • Some tools and technologies that are relevant: Transformers, Language Models, Spacy, Keras, Tensorflow, Pytorch, Numpy, SageMaker, Vertex AI, FAISS, NMSLIB, ScaNN, OpenSearch, ElasticSearch, Vector Databases, Similarity Search, Graph Neural Nets, Deep Graph Library, Pytorch Geometric


  • Comprehensive Health benefits
  • 401k Matching
  • Workspace benefits for your home office
  • Personal & Professional development funds
  • Family Planning Support
  • Flexible Vacation (please use them!) & Reddit Global Days Off
  • 4+ months paid Parental Leave
  • Paid Volunteer time off

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

To provide greater transparency to candidates, we share base pay 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 pay range for this position is: $188,800 - $283,200 .