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Senior Data & Machine Learning Engineer

True Talent Solutions Partners New York, New York, United States · $200K–$300K/yr

Yesterday
machine-learning Principal (10+ yrs) Full-time United States
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About the role

Build and operate end-to-end recommendation and ad-matching systems, including retrieval, ranking, embeddings, real-time serving, feature stores, and reliable data pipelines. Apply language and foundation models to user and content understanding, measure recommendation performance, and lead projects from prototype to production in partnership with company and engineering leadership.

What they look for

Recommendation Systems Ranking Systems Ad Matching Machine Learning Embedding-Based Retrieval Vector Search Real-Time Inference Feature Stores SQL Data Pipelines ETL/ELT dbt Postgres Language Models Online Learning Dashboarding

Requirements

Candidates need at least three years of experience with recommendation, ranking, or advertising systems, with typically five to sixteen years of overall experience and production experience across the recommendation lifecycle. They should have hands-on experience with embeddings and real-time vector search, strong SQL and data-pipeline skills, and the ability to work independently; startup experience and ML team leadership are useful.

Full description

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.

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