Reddit is looking to improve its ad ranking, bidding, measurement, and optimization systems to deliver more relevant ads and drive value for advertisers.
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.
- Experience working in the Ads domain
- Familiarity with distributed systems and large-scale data processing technologies (e.g., Spark, Kafka).
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.
Other
- Experience or interest in the advertising business and understanding customer needs
- An advanced degree (MS/PhD) in a quantitative field.
