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

As a Data Scientist, you'll analyze complex datasets to optimize fraud authentication, design ML solutions, and collaborate with cross-functional teams.

The role involves leading data science initiatives, building machine learning models, conducting experiments, and collaborating with teams to enhance customer experiences and business outcomes.

Lead the Design of Experiments center of excellence, standardizing incrementality measurement, building testing infrastructure, and mentoring Data Scientists while optimizing customer experience and validating product initiatives.

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

Lead cross-functional teams to develop and deploy AI-powered products, focusing on model training, inference, and system optimization. Innovate AI solutions that enhance banking experiences and use cutting-edge technologies to lead in AI engineering.

As a Senior Lead AI Engineer, you'll design and support AI systems, collaborating with teams to enhance customer interactions and deliver AI-powered products.

Lead AI Engineer role involves creating AI systems, optimizing performance, and collaborating with cross-functional teams to innovate banking solutions using AI technologies.

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, 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.