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

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.

• 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

• 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)