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

Lead a team of data scientists to develop AI/ML solutions, leveraging advanced technologies for customer interactions and product innovations. Build and implement NLP models for large-scale applications while collaborating with cross-functional teams.

The Senior Lead AI Engineer will develop, test, and support AI software, design new models, and enhance AI product offerings at Capital One while collaborating across teams.

The Senior Lead AI Engineer will develop and support AI software components, collaborate with cross-functional teams, and enhance banking experiences through AI systems.

The role involves architecting and launching AI systems, designing software components, optimizing performance, and collaborating with cross-functional teams to enhance customer experiences at Capital One.

The Lead Machine Learning Engineer will design, build, and deploy machine learning models and data pipelines, ensuring high performance and governance of ML applications while collaborating in an Agile environment.

Lead AI Engineer responsible for developing AI software components, partnering with cross-functional teams to deliver AI-driven products, and optimizing large-scale AI systems.

The Senior Lead AI Engineer will develop AI software components, partner with cross-functional teams, and contribute to AI system optimization. Key responsibilities include model training, deployment, and leveraging AI technologies to enhance banking services.

The Applied Researcher I will partner with cross-functional teams to develop AI-powered products, conduct applied research, and build AI foundation models using emerging technologies.

The Lead Machine Learning Engineer designs and implements ML applications, builds data pipelines, collaborates with teams, and ensures performance and governance of ML systems.

Partner with cross-functional teams to build and deploy machine learning models across the credit card lifecycle. Use Python, cloud and big-data tools to analyze large numeric and textual datasets, design/train/validate models, and translate insights into business-driven product decisions for marketing, underwriting, and fraud prevention.