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

The Director of Data Science role at Capital One involves leading a team to build data pipelines and machine learning models, leveraging technologies like Python and AWS to derive insights for improving customer financial decisions.

Lead cross-functional teams to develop and deploy AI-powered products, improve AI system performance, and create innovative AI solutions at Capital One.

The role involves partnering with a cross-functional team to develop AI-powered products, applying state-of-the-art AI research, and delivering models at scale.

This role involves leading the development of AI-powered products, optimizing large scale AI systems, and mentoring cross-functional teams. It focuses on designing and deploying AI components, contributing to the technical vision, and applying cutting-edge AI techniques.

The Lead Machine Learning Engineer will design, build, and productionize ML applications, oversee model performance, collaborate with teams, and ensure reliable deployment of ML systems at scale.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Partner cross-functionally, invent LLM optimization techniques, and contribute to technical vision and roadmap for foundational AI infrastructure.

Lead design, build, deploy, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize production LLM performance (cost, latency, throughput) and contribute to long-term technical vision.

Lead and mentor applied research teams to design, train, evaluate, validate, and deploy large-scale AI foundation models. Partner with cross-functional product and engineering teams to deliver production AI platforms, perform high-impact applied research, scale training and inference, and represent Capital One in the research community.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize LLM performance and scalability, partner with cross-functional teams, and contribute technical vision and roadmap for foundational AI systems.

Design, build, deploy, and maintain production ML systems and data pipelines at scale. Lead cross-functional teams to implement ML architectures, ensure model performance and governance, automate CI/CD for models, and leverage cloud platforms and ML frameworks to deliver reliable, explainable solutions.