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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.
Responsibilities
- 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.
Requirements
- At least 3 years of experience with recommendation, ranking, or advertising systems.
- 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.
- Strong SQL skills and experience building data pipelines and transformation layers with dbt or similar tools, plus Postgres or columnar analytical databases.
- Early-stage startup or founder experience is valued.
- Experience building an ML team is relevant.
- Graduate study in computer science or machine learning is relevant.
Skills
- Embeddings
- Real-time vector search tools (FAISS, Milvus, Pinecone, pgvector, or similar)
- Large language models
- Foundation models
- dbt
- Postgres
- Columnar analytical databases
Location
- New York City area
- Nearby U.S. time zone
Work Type
- Hybrid
Experience Level
- 3+ years with recommendation, ranking, or advertising systems
- 5-16 years overall experience
Education Level
- Graduate study in computer science or machine learning
Salary/Compensations
- $200,000 to $300,000 annually
Benefits
- Visa sponsorship is not available