Senior Data & Machine Learning Engineer

Role details

ABOUT THE ROLE Own the recommendation and matching stack end to end at an early-stage AI company in the advertising and consumer modeling space. You will build the models, real-time serving systems, and data platform that power personalized ad selection. WHAT YOU'LL DO - Build retrieval, ranking, and re-ranking systems for matching 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 and serving path, including offline training, online inference, and pipeline reliability. - Apply language models and foundation models to subscriber tagging, content understanding, and user modeling. - Lead projects from prototype to production, including online learning, feedback loops, ETL/ELT pipelines, and warehouse transformations. - Create dashboards and automated scorecards for performance and key recommendation metrics. - Partner with company and engineering leadership on priorities, and help grow the ML function over time. WHAT WE'RE LOOKING FOR - At least 3 years of experience with recommendation, ranking, or advertising systems, and typically 5 to 16 years of overall experience. - Production experience building a recommendation or matching system across candidate generation, ranking, embedding-based retrieval, serving, and evaluation. - Experience with ad ranking, click-through or conversion prediction, or ad matching. - Hands-on experience with embeddings and real-time vector search tools such as FAISS, Milvus, Pinecone, or pgvector. - Strong SQL skills and experience building data pipelines and transformation layers with dbt or similar tools, plus Postgres or analytical databases. - Ability to work independently in a high-autonomy environment; early-stage startup experience and prior ML team leadership are useful. COMPENSATION & BENEFITS Base salary: $200,000 to $300,000 annually. Visa sponsorship is not available. LOCATION Hybrid, based in New York, New York. Candidates in a nearby US time zone should be able to travel to New York quarterly.