Staff Software Engineer, Machine Learning (Prediction)

Remote - British Columbia, Canada

Full Time Senior-level / Expert USD 62K - 115K *


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Reddit is a community of communities where people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to bring community, belonging, and empowerment to everyone in the world. Reddit users submit, vote, and comment on content, stories, and discussions about the topics they care about the most. From pets to parenting, there’s a community for everybody on Reddit and with over 50 million daily active users, it is home to the most open and authentic conversations on the internet. For more information, visit

Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly and will continue to be after the pandemic. 

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!

Ads prediction team is the central team to handle machine learning needs in the ads delivery pipeline.   Some examples projects that the team own:

  • Improve our model through systematic model architecture engineering work including exploring different deep neural network architectures
  • Systematic feature engineering work to build power features from Reddit’s data with aggregation, embedding, content understanding techniques
  • Developing highly efficient retrieval ranking models with good balance between model performance and computation efficiency 

As a Staff Machine Learning Engineer in the ads prediction team, you will research, formulate and execute on our mission to deliver the right ad to the right user under the right context with data and ML driven solutions.


  • Building industrial level models for critical ML tasks with advanced modeling techniques
  • Research, implement, test, and launch new model architectures including deep neural networks with advanced pooling and feature interaction architectures
  • Research, implement, test, and launch new model architectures to handle retrieval ranking tasks with a good balance between model performance and computation efficiency
  • 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.

Required Qualifications:

  • 2+ years of experience with industry-level deep learning models
  • 5+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch)
  • 5+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models
  • 5+ years of experience of orchestrating complicated data generation pipelines on large-scale dataset
  • Experience with Ads domain is a plus
  • Experience with recommendation system is a plus


  • 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

Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at

* Salary range is an estimate based on our salary survey 💰

Tags: Deep Learning Engineering Feature engineering Industrial Machine Learning Pipelines PyTorch Research TensorFlow Testing

Perks/benefits: Career development Flex vacation Health care

Regions: Remote/Anywhere North America
Country: Canada
Job stats:  24  5  0
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