Senior Data & Machine Learning Engineer

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.