Top Artificial Intelligence Data Engineering Jobs in New York City, NY

As a Data Architect at RapidScale, you'll lead data platform engagements, ensuring delivery quality, managing teams, and designing cloud architectures while supporting ML implementations and client interactions.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

As a Data Product Operations Lead, you'll design and scale audio data pipelines, ensuring high-quality dataset production while collaborating with researchers and cross-functional teams.

As an Engineering Manager, you'll lead efforts to enhance model performance, manage team projects, and support professional growth in a dynamic environment.

Design and build data pipelines using AWS services and Python. Collaborate with data teams to ensure data quality and optimize performance.

As a Data Engineer, design and maintain data pipelines, ensure data quality, and support AI workflows using modern tools and cloud environments.

The Senior Data Engineer will design and manage data pipelines for massive datasets, ensuring quality, cost management, and effective data operations. Responsibilities include overseeing data flows, monitoring data quality, and managing vendor partnerships.