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Open nowFirst seen 44 hours ago

Senior Data & Machine Learning Engineer – NYC (Hybrid) PTQ

Sivad Consulting47 open roles

Where
New York, New York, United States
Work mode
Hybrid
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Your applicationOpen nowSenior Data & Machine Learning Engineer – NYC (Hybrid) PTQSivad Consulting · New York, New York, United States

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Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 44 hours ago

The posting

Senior Data & Machine Learning Engineer – NYC (Hybrid) PTQ

$200k - $300k

We're looking for a Senior Data & Machine Learning Engineer who can independently own the matching stack end-to-end. You'll work directly with the engineering team to build the models, the serving path, and the platform underneath them.

This is a high-autonomy position. You won't be handed a roadmap of analyses to run. You'll look at the data, identify what matters, form your own hypotheses, and design experiments to test them. The best candidate thinks like a scientist and builds like an engineer.

Responsibilities

  • Retrieval, ranking, and re-ranking for ad-to-recipient matching.
  • The embedding and vector-search infrastructure powering real-time ad selection inside publisher newsletters.
  • Multi-objective optimization in a single ranking stack: CTR lift, advertiser ROAS, publisher revenue, and subscriber relevance.
  • The feature store and the serving path: offline training, online inference, and the parity between them. Pipeline health is your problem, not someone else's.
  • LLMs and foundation models applied to subscriber tagging, content understanding, and user modeling.
  • Lead 0-to-1 initiatives from prototype to production, including online learning and feedback-loop systems, reliable ETL/ELT pipelines, and the dbt/warehouse transformation layer
  • Dashboards and automated scorecards giving the team and leadership real-time visibility into performance, CTR lift, tag coverage, and other key metrics.
  • Work closely with the CTO, CEO, and engineering team to set priorities and the order of work for scaling the recommendation system
  • Grow into a leadership role, with a path to building and running an ML team

Work Experience and Requirements

  • 3+ years of experience with recommendation,​ ranking,​ or ads systems
  • 5 -​ 16 years of experience in production ML or data engineering
  • Has owned multiple layers of a recommendation system end-to-end (retrieval,​ ranking,​ serving,​ evaluation),​ not one component on a large team
  • Recsys models for ads:​ ads ranking,​ CTR or conversion prediction,​ or ad matching
  • Embeddings and real-​time vector-​search infrastructure (FAISS,​ Milvus,​ Pinecone,​ pgvector or similar)
  • Founder background or early-​stage startup experience
  • Based in the NYC area,​ OR in a US time zone close to Eastern,​ and can travel to NYC quarterly
  • Built and maintained their own data pipelines and transformation layer in SQL and dbt (or similar)
  • Previous experience building an ML team
  • Education
  • Master's or Ph.​D.​ in Computer Science / Machine Learning preferred (helpful but not required)
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