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Senior Machine Learning Engineer, Ads Engagement Modeling

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 97M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

We're committed to hiring the best talent and building a diverse team. We're proud to be completely remote-friendly and will continue to offer remote work options beyond the pandemic.

As a company, Reddit primarily generates revenue through advertising, and we're working towards building a massive business to fund our mission. We distinguish ourselves from other digital ad platforms by attracting advertisers who want to connect with a specific target audience because of our passionate and engaged communities. 

The Ads Engagement Modeling team is responsible of predicting ads engagement rates used in auctions for upper and middle funnel ad products. The team focuses on Click-Through Rate (CTR) prediction to optimize ad engagement and marketplace efficiency, particularly for Reddit’s most critical ad product: CPC (Cost-Per-Click). Additionally, the team manages video view modeling, landing page optimization, and pCTR (predicted CTR) models for product ads

The Engagement Modeling team collaborates closely with both upstream and downstream teams to drive the development of new features and model iterations, continually improving ranking models for upper and middle funnel products.

Project highlights:

  • Model Architecture Engineering: Explore and implement state-of-the-art architectures such as multi-task learning and calibration models.
  • Systematic Feature Engineering: Develop powerful features from Reddit’s data using techniques like aggregation, embedding, sub-models, and content understanding.
  • Zero-to-One Model Development: Build models from scratch, collaborating with cross-functional teams on Go-To-Market strategies for vertical products like video view models, landing page optimization, and product ads.

As a Senior Machine Learning Engineer on the Engagement Modeling team, you will be responsible for researching, formulating, and executing projects, while actively contributing to the end-to-end implementation process. You will work closely with cross-functional teams to ensure the successful delivery of products. This role also offers the opportunity to leverage your expertise and help shape the future of ads ML at Reddit.

Your Responsibilities:

  • Build industry-level models for critical machine learning tasks, applying advanced modeling techniques.
  • Research, implement, test, and launch innovative model architectures, including deep neural networks with advanced pooling and feature interaction designs.
  • Conduct systematic feature engineering to transform diverse raw data from Reddit (dense, sparse, behavioral, content, etc.) into actionable features using techniques such as aggregation, embedding, sub-models, and more.
  • Serve as a mentor and advocate across teams, fostering collaboration and knowledge sharing.
  • Contribute meaningfully to the team’s strategic direction. We value everyone’s input and encourage active participation in shaping our future roadmap.

Who You Might Be:

  • Proven track record of driving KPI improvements through strategic work in model architecture and feature engineering.
  • 3+ years of experience building industry-level deep learning models.
  • 3+ years of experience with mainstream ML frameworks, such as TensorFlow and PyTorch.
  • 4+ years of hands-on experience with the full lifecycle of training, evaluating, testing, and deploying industry-level models.
  • Experience iterating large-scale neural network models in a production environment is a must.
  • Familiarity with the Ads domain is a strong plus.

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

Join us at Reddit, and help us build a community that is inclusive and empowering for everyone.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  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 ApplicationAssistance@Reddit.com.

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Reddit Canada Equal Employment Information

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. To bring community and belonging to everyone in the world, Reddit’s employees must represent communities and redditors on our platform.

The Company is committed to treating all people in a way that allows them to maintain their dignity and independence. We believe in integration and equal opportunity. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process.

We will work with all applicants to accommodate their individual accessibility needs

Our vision at Reddit is to have a workforce representative of people with different perspectives and experiences, including but not limited to, gender, race and ethnicity, sexual orientation, age, national origin, religion, and political views.

We invite you to self-identify across the identities below so we can better understand our talent pools and assess our effectiveness in attracting and recruiting people to Reddit from all backgrounds.

Answering these questions will not impact your application, nor will this information be shared with anyone making a hiring decision.

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