Senior Machine Learning Engineer, Ads

Reddit has a flexible 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 in any country in which we have a physical presence.
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!

Reddit is poised to rapidly innovate and grow like no other time in its history. We’re currently hiring across multiple teams including: Ads Prediction, App Ads & Conversion Modeling, Ads Measurement Modeling, Ads Targeting & Retrieval, Advertiser Optimization and Ads Marketplace Teams.
Ads ML Serving Team
Part of Reddit’s Ads ML Platform, this team builds a highly reliable, scalable, and efficient ML serving stack. They focus on long-term architecture, tight integration with the ads serving stack, CPU/GPU performance optimization, and model velocity tools like observability libraries and quality gating.

Attribution & Identity Team
This team builds attribution systems and identity solutions that help advertisers measure the impact of their campaigns. They create experimentation tools and platforms that improve usability, transparency, and performance insights.

Ads Measurement Modeling Team
A horizontal ML team in the Ads Measurement org focused on proving Reddit Ads value while maintaining privacy compliance. Their work includes Modeled Identity, Modeled Conversions, and ATT opt-out utility enhancements.

Ads Targeting and Retrieval Team
This team designs and implements large-scale ML systems to improve targeting products. They work on offline and online retrieval systems to enhance contextual and behavioral targeting.

Advertiser Optimization Team
Composed of two horizontal teams, this group focuses on advertiser outcomes. The Recommendations and Forecasting team builds ML-driven tools for advertisers and sales. The Bidding/Pacing team develops algorithms and products like TCPA, TROAS, and performance advertising solutions, while driving innovations in marketplace dynamics.

Ads Marketplace Quality Team
This team optimizes Reddit’s ads marketplace by building algorithms for auction and pricing efficiency. They also work on supply optimization and ad relevance, ensuring ads reach the right users at the right time in the right context.

App Ads and Conversion Modeling Teams
Formed in early 2024, these teams focus on app ads modeling, including app install models and deep neural network models for iOS and Android conversions. They work on in-app event optimization and return on ad spend (RoAS) optimization, and are running experiments on top of DNN architectures to improve prediction accuracy.

Ads Prediction Team
This team drives innovation across signals, features, model architecture, and infrastructure to improve marketplace efficiency and revenue. It includes:

• Core Ads Ranking (CAR): Builds reusable, scalable features and ranking models that integrate across the ads ecosystem, improving quality and iteration speed.
• Engagement Modeling (EV): Develops click, long-click, and video engagement models for upper- and middle-funnel ad products.
  

Reddit Ads offers the opportunity to work on large-scale systems that directly impact advertisers, users, and revenue. We have openings across multiple teams and are looking for engineers and ML experts at all levels.

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.

• 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.

• 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.

• 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).