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)