Senior Data, Machine Learning Engineer

SIVAD Consulting

. Own the matching stack end-to-end .

Posted 10/22/2026full-timeNew York City • New York • United StatesSenior💰 $200,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing recommendation systems, including retrieval, ranking, and serving paths. Proficient in managing data pipelines and applying machine learning models to enhance ad matching and user modeling.

Highest-signal resume keywords

Recommendation System OwnershipProduction Machine Learning ExperienceReal-Time Vector-Search InfrastructureData Pipeline DevelopmentLeadership in Machine Learning Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Recommendation SystemsRanking ModelsCTR PredictionAd MatchingEmbeddingsSQLDbtETLOnline LearningFeedback-Loop Systems

Soft Skills

LeadershipCollaborationCommunication

Tools & Technologies

FAISSMilvusPineconePgvectorDashboardsAutomated Scorecards

Certifications & Qualifications

Master's in Computer SciencePh.D. in Machine Learning

Industry Keywords

Ad SystemsData EngineeringMachine LearningStartup ExperienceNYC Area

Tech Stack

Tools & technologies

ETLSQL

About the role

Key responsibilities & impact

Own the matching stack end-to-end
Build models, the serving path, and the underlying platform
Develop retrieval, ranking, and re-ranking for ad-to-recipient matching
Build embedding and vector-search infrastructure for real-time ad selection in publisher newsletters
Optimize CTR lift, advertiser ROAS, publisher revenue, and subscriber relevance in a unified ranking stack
Own the feature store and serving path, including offline training, online inference, and training-serving parity
Maintain pipeline health
Apply LLMs and foundation models to subscriber tagging, content understanding, and user modeling
Lead 0-to-1 initiatives from prototype to production, including online learning, feedback-loop systems, reliable ETL/ELT pipelines, and dbt/warehouse transformation
Build dashboards and automated scorecards for real-time visibility into performance, CTR lift, tag coverage, and other key metrics
Work with the CTO, CEO, and engineering team to prioritize and sequence scaling work for the recommendation system
Grow into a leadership role with a path to building and running an ML team

Requirements

What you’ll need

3+ years of experience with recommendation, ranking, or ads systems
5–16 years of experience in production ML or data engineering
End-to-end ownership of multiple layers of a recommendation system: retrieval, ranking, serving, and evaluation
Experience with recommendation-system models for ads, including ads ranking, CTR or conversion prediction, or ad matching
Experience with embeddings and real-time vector-search infrastructure such as 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, with ability to travel to NYC quarterly
Experience building and maintaining data pipelines and a transformation layer in SQL and dbt or similar
Previous experience building an ML team
Master's or Ph.D. in Computer Science / Machine Learning preferred, but not required

Benefits

Comp & perks

Path to building and running an ML team
High-autonomy position with ownership of the matching stack end-to-end