Machine Learning Engineer

Summary

Join Reddit's Ads team as a Machine Learning Engineer and significantly contribute to the company's business growth. This hands-on role encompasses the entire ML system lifecycle, from initial research and modeling to deployment and optimization. You will design, build, and deploy machine learning models to solve critical problems in ad ranking, bidding, and optimization, taking full ownership of the ML lifecycle. Responsibilities include systematic feature engineering, collaboration with cross-functional teams, and enhancing the reliability and stability of ML systems. The ideal candidate will have a proven track record of using machine learning to achieve KPI wins and solve complex problems. This position offers the opportunity to research new algorithms and contribute to the team's strategy and roadmap.

Requirements

• 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

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

Preferred Qualifications

• 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)