Senior Machine Learning Engineer, Ads

Overview Join to apply for the Senior Machine Learning Engineer, Ads role at Reddit, Inc. 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. Reddit users submit, vote, and comment on the topics they care most about. Reddit is evolving and continuing its 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. The year ahead is a busy one. 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. Team description and teams Reddit is hiring across multiple Ads 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 ML serving stack, focusing on long-term architecture, tight integration with the ads serving stack, CPU/GPU performance optimization, and model velocity tools, observability libraries, and quality gating. Attribution & Identity Team — Builds attribution systems and identity solutions to measure campaign impact, with experimentation tools and platforms to improve usability, transparency, and performance insights. Ads Measurement Modeling Team — Horizontal ML team focused on proving Reddit Ads value while maintaining privacy compliance; work includes Modeled Identity, Modeled Conversions, and ATT opt-out utility enhancements. Ads Targeting and Retrieval Team — Designs and implements large-scale ML systems to improve targeting products, including offline and online retrieval systems for contextual and behavioral targeting. Advertiser Optimization Team — Composed of two horizontal teams focusing 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 — Optimizes Reddit’s ads marketplace through auction and pricing algorithms, supply optimization, and ad relevance enhancements. App Ads and Conversion Modeling Teams — Focus on app ads modeling, including install models and deep neural network models for iOS and Android conversions, in-app event optimization, RoAS optimization, and experimentation on top of DNN architectures to improve prediction accuracy. Ads Prediction Team — Drives innovation across signals, features, model architecture, and infrastructure to improve marketplace efficiency and revenue; includes Core Ads Ranking (CAR) and Engagement Modeling (EV) with specific responsibilities described below. The Ads Creative Effectiveness team — Newly formed group focused on improving ad creative through generative and predictive products, training and tuning LLMs/VLMs, building performance predictors, and guiding advertisers towards best practices. This team is central to Reddit’s creative strategy. Role Description Join the Ads team as a Machine Learning Engineer and contribute to the full lifecycle of ML systems, from research and modeling to deployment and production optimization. Your work will impact how we deliver relevant ads and drive value for advertisers in areas such as 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 scalable serving systems and production model maintenance. Perform systematic feature engineering to transform raw, diverse data into high-quality features that drive model performance. Collaborate with product managers, data scientists, and engineers to translate business challenges into ML solutions. Improve reliability and stability of 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. Qualifications At least 3+ years of end-to-end experience in training, evaluating, and deploying machine learning models in production. Proficient in one or more general-purpose programming languages (e.g., Python, Scala) and solid software development practices. Hands-on experience with a major ML framework (e.g., TensorFlow, PyTorch) and a strong understanding of core ML concepts and algorithms. Proven ability to work effectively with cross-functional teams to translate business needs into technical solutions. Track record of using ML to drive KPI wins and solve complex real-world problems. Bonus Points Experience in the Ads domain Interest in the advertising business and understanding customer needs Advanced degree (MS/PhD) in a quantitative field Familiarity with distributed systems and large-scale data processing technologies (e.g., Spark, Kafka) We respect candidate privacy and outline data handling in our Candidate Privacy Policy. Interviews may be recorded in select roles/locations with an opt-out option. Personal information categories collected include identifiers and employment-related information. We will not sell or disclose your data for marketing. Recordings may be deleted after a hiring decision is made. Reddit is proud to be an equal opportunity employer and provides reasonable accommodations for qualified individuals with disabilities. If you need an accommodation during the interview process, please inform your recruiter. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries: Social Networking Platforms Referrals increase your chances of interviewing at Reddit, Inc. by 2x. #J-18808-Ljbffr