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

The Applied Researcher I role involves developing AI foundation models, collaborating with cross-functional teams, and conducting advanced research to enhance banking experiences with AI.

Lead a team to analyze data, create machine learning models, and deliver insights for customer-focused financial products, leveraging various technologies.

The role involves leading a team to develop personalized recommendation systems using machine learning, working with large datasets, and collaborating across disciplines.

The Senior Lead AI Engineer will develop and support AI components, lead a cross-functional team, and drive innovation in AI systems at Capital One.

As a Lead AI Engineer, you will design, develop, and support AI software components while partnering with cross-functional teams to deliver AI-powered products at Capital One.

The role involves building machine learning models, collaborating with teams, and leveraging technology to analyze data, ultimately enhancing credit underwriting for business cards.

The Applied Researcher II will develop AI-powered products, partner with cross-functional teams, engage in applied research, and implement AI foundation models.

Lead and deliver ML solutions for bank operations, partnering with cross-functional teams to design, train, validate, and deploy large-scale models (NLP, forecasting, anomaly detection) using cloud and open-source tools, and mentor technical talent.

Lead design, build, and productionize scalable ML models and pipelines. Collaborate with product and data science teams, implement cloud-based architectures, ensure CI/CD, monitoring, model governance, and responsible AI practices.

Lead design, development, deployment, and support of foundation model training and LLM inference platforms. Build similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, and scalability; contribute to technical vision and roadmap while partnering across engineering, research, product, and program teams.