Machine Learning Engineer, Ads

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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 redditinc.com.

Reddit is a network of more than 100,000 communities where people can dive into anything through experiences built around their interests, hobbies and passions. 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 more than 100 million daily active uniques, it is home to the most open and authentic conversations on the internet. For more information, visit redditinc.com.

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!

Team Description

Reddit is poised to rapidly innovate and grow like no other time in its history. We’re currently hiring across multiple teams including: Ads Measurement Modeling, Ads Targeting & Retrieval, Advertiser Optimization and Ads Marketplace Teams.

Ads Measurement Modeling Team
This horizontal ML team in the Ads Measurement org works on proving the value of Reddit Ads to advertisers while ensuring privacy compliance. Their projects address challenges in signals, privacy, and identity, including Modeled Identity, Modeled Conversions, and enhancements for ATT opt-out utility.

Ads Targeting and Retrieval Team
This team designs and builds large-scale ML systems to improve targeting products. Their work spans offline and online retrieval systems that enhance contextual and behavioral targeting, helping advertisers reach the most relevant audiences.

Advertiser Optimization Team
This group consists of two horizontal teams focused on advertiser outcomes. The Recommendations and Forecasting team builds ML-driven tools for advertisers and sales, while the Bidding/Pacing team develops algorithms and customer-facing products like TCPA, TROAS, and performance advertising solutions. They work on marketplace dynamics, bidding and pacing innovations, and new advertiser tools.

Ads Marketplace Quality Team
This team improves the efficiency of Reddit’s ads marketplace by developing algorithms for auction and pricing optimization, directly impacting advertiser and user value. They also contribute to strategic initiatives such as supply optimization and ad relevance, with the goal of showing the right ads to the right users at the right time and in the right context.

Role Description

Join the Ads team as a Machine Learning Engineer and become a key contributor to Reddit’s business. In this hands-on role, you will be responsible for the full lifecycle of our ML systems, from initial research and modeling to deployment and optimization in production. Your work will directly impact how we deliver relevant ads and drive value for our advertisers across areas like ad ranking, bidding, measurement, and optimization.

Responsibilities:

• Design, build, and deploy industrial-level machine learning models to solve critical problems in ad ranking, bidding, and optimization.
• Take full ownership of the ML lifecycle, from ideation and research to building scalable serving systems and maintaining models in production.
• Perform systematic feature engineering to transform raw, diverse data into high-quality features that drive model performance.
• Work closely with product managers, data scientists, and engineers to translate business challenges into effective ML solutions.
• Improve the reliability and stability of our ML systems by building robust monitoring, alerting, and automated retraining pipelines.
• Research new algorithms, stay up-to-date with state-of-the-art ML techniques, and contribute to the team’s strategy and roadmap.

Required Qualifications:

• At least 3+ years of end-to-end experience in training, evaluating, and deploying machine learning models in a production environment.
• Proficient in one or more general-purpose programming languages (e.g., Python, Scala) and have a solid understanding of software development best practices.
• Hands-on experience with a major machine learning framework (e.g., TensorFlow, PyTorch) and a deep understanding of core ML concepts and algorithms.
• Proven ability to work effectively with cross-functional teams, including product managers and data scientists, to translate business needs into technical solutions.
• Track record of using machine learning to drive key performance indicator (KPI) wins and solve complex, real-world problems.

Bonus Points:

• Experience working in the Ads domain 
• Experience or interest in the advertising business and understanding customer needs
• An advanced degree (MS/PhD) in a quantitative field.
• Familiarity with distributed systems and large-scale data processing technologies (e.g., Spark, Kafka).

In select roles and locations, the interviews will be recorded, and transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out recording, transcription and summarization prior to any scheduled interviews.

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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, due to a disability, you need an accommodation during the interview process, please let your recruiter know.