data · machine learning
ABOUT THE ROLE
Join a small, early-stage AI team building a recommendation system for personalized advertising. You will own the matching stack end to end, from data and models through real-time serving, and help shape the system's technical priorities as it scales.
WHAT YOU'LL DO
- Build retrieval, ranking, and re-ranking systems to match ads with recipients.
- Develop embedding and vector-search infrastructure for real-time ad selection.
- Optimize ranking across click-through rate, advertiser return, publisher revenue, and subscriber relevance.
- Own the feature store, offline training, online inference, serving path, and pipeline health.
- Apply large language models and foundation models to subscriber tagging, content understanding, and user modeling.
- Take initiatives from prototype to production, including online learning, feedback loops, ETL/ELT pipelines, and warehouse transformations.
- Create dashboards and automated scorecards to track performance and key metrics.
- Partner with company leadership and engineering to set priorities, with an opportunity to grow into leading an ML team.
WHAT WE'RE LOOKING FOR
- At least 3 years of experience with recommendation, ranking, or advertising systems, and 5 to 16 years of overall experience.
- Production experience owning recommendation or matching systems across candidate generation, ranking, embedding-based retrieval, serving, and evaluation.
- Experience building ad ranking, click-through or conversion prediction, or ad-matching models.
- Hands-on experience with embeddings and real-time v