Top AI & Machine Learning Jobs in New York City, NY

The Lead AI Engineer will develop AI solutions, partner with cross-functional teams, and optimize large-scale production AI systems using various technologies.

The Applied Researcher I will partner with teams to deliver AI products, leverage technologies to analyze data, and build foundation models. This role includes engaging in applied research and translating technical findings into business goals.

The Senior Lead AI Engineer will collaborate with cross-functional teams to design, develop, and implement AI software solutions, focusing on large-scale production systems and AI model optimization.

As a Principal Associate Data Scientist, you'll build and manage machine learning models for marketing efficiency, translating business goals into data solutions and collaborating with stakeholders.

As a Lead AI Engineer, you will develop, deploy, and support AI software components, collaborate with cross-functional teams, and optimize performance of large-scale AI systems.

The Lead AI Engineer will design, develop, deploy, and support AI software components, collaborating with cross-functional teams to create scalable AI solutions that enhance customer interactions and operational efficiency.

In this role, you will develop AI foundation models, conduct applied research, and collaborate with cross-functional teams to enhance customer experiences through AI-powered products.

The Lead AI Engineer will develop and deploy AI software components, optimize AI systems, and collaborate with cross-functional teams at Capital One to enhance customer interactions through AI technology.

The Senior Lead AI Engineer will design, develop, and support AI systems, leveraging machine learning technologies to enhance customer experiences and optimize AI performance.

Lead a team building AI-native, governed engineering harnesses and full-stack microservice systems. Design agentic orchestration, typed contracts, observability, CI/CD integration, and developer tooling to enable safe, auditable LLM-driven workflows in cloud environments.