data
Posted Mar 19Staff Machine Learning Engineer, Ads Auction (Ads Marketplace Quality)
at Redditinc
United StatesRemote
Responsibilities
- Lead and oversee the strategy development, quarterly planning and day-to-day execution of initiatives related to ads marketplace, auction and pricing.
- Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—that optimizes the ads marketplace efficiency.
Requirements
- With 100,000+ active communities and approximately 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
- 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.
- The Ads Marketplace Quality team is growing and we are looking for an experienced machine learning engineer and domain expert to be part of the journey of developing a world-class marketplace and optimizing for users, advertisers and Reddit value.
- You will develop a deep understanding of our marketplace dynamics and identify areas of improvements by getting to the bottom of data, design, implement and ship algorithms to production that improve our ads marketplace efficiency.
- As a Staff Machine Learning Engineer in the Ads Marketplace Quality team, you will be an industry technical leader with domain knowledge in ads marketplace dynamics, auction and pricing, you will research, formulate, and execute on our mission to build end-to-end algorithmic solutions and deliver values to all the three-sided participants to our marketplace.
- Proactively further our understanding of marketplace dynamics and develop algorithms to improve the efficiency and effectiveness of our ads marketplace, auction and pricing.
- experience with industry-level product development, with at least 5+ years focused on data-driven, marketplace-optimization problem space at scale.
- Strong knowledge of ads marketplace optimization. Demonstrated
- Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink).
- Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference.
- Proficiency with programming languages (Java, Python, Golang, C++, or similar) and statistical analysis.
- Additionally, Reddit offers a wide range of