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Senior Machine Learning Engineer - Ads Targeting

Remote - Ontario, Canada
Software Development

Reddit has a flexible first workforce! if you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the United States or Canada.

Ads Targeting ML engineers are focused on designing and implementing ML systems and solutions for improving targeting products. The team’s projects involve building large-scale offline & online retrieval systems across several dimensions to improve contextual & behavioral targeting for targeting products.

As a senior machine learning engineer in the ads targeting core team, you will execute our mission to automate targeting and deliver the most relevant audiences to advertisers under the right context with data and ML-driven solutions. 

Your Responsibilities:

  • Own end-to-end execution of ML-based targeting products like auto targeting, user lookalikes etc
  • Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two tower models) with a focus on improving advertiser outcomes
  • Own offline & online experimentation of ML models for improving targeting products to drive advertiser outcomes
  • Drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy
  • Work on large scale data systems, and product integration
  • Collaborate closely with multiple stakeholders cross product, engineering, research and marketing 

Required Qualifications

  • Experience with ads retrieval modeling, ranking or recommendation systems 
  • 5+ years of end-to-end experience of training, evaluating, testing, and deploying machine learning models
  • 2+ years of experience building machine learning models with Tensorflow/Pytorch 
  • Experience with large scale data processing & pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQuery
  • Experience working with nearest-neighbor search systems is a big plus
  • Experience working with cross functional stakeholders across research, product & infrastructure to productize ML research 
  • Experience with deep learning, representation learning or transfer learning is preferred
  • Tech lead experience in a product team is strongly preferred

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
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