• 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 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.
• The Ads Creative Effectiveness team

This team is a newly formed group aimed at improving ad creative at Reddit through generative and predictive products. We train, adapt and finetune LLMs/VLMs to help advertisers make impactful images, videos and text. We build performance predictors to understand and rank ad components, ensuring the advertiser ships the best possible campaigns. We construct insight and recommendation engines to guide advertisers towards best practices and key enhancements, distilling knowledge about what works at Reddit to supercharge their performance.This team is at the heart of Reddit’s creative strategy, a core priority for the organization.

• 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.
• 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 .

• 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:
• Experience working in the Ads domain
• At least 3-5+ 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 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).

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave
• In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors .

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.