Machine Learning Engineer, Ads

About Reddit

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 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. Our mission is 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.

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.

Team Description

Reddit is poised to rapidly innovate and grow like no other time in its history. We’re currently hiring across multiple Ads 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.
• Ads Creative Effectiveness Team: This newly formed group aims 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.

Role Description

Join the Ads team as a Machine Learning Engineer, Ads 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).

Benefits

• 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.

Key skills/competency

• Machine Learning
• Ad Ranking
• Bidding Optimization
• Feature Engineering
• Production ML Systems
• Python/Scala
• TensorFlow/PyTorch
• Distributed Systems
• Data Processing
• Algorithm Research