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

Design, develop, deploy, optimize, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture and cost-performance optimization across scalable AI platforms, establish engineering standards, contribute to long-term technical roadmaps, and mentor senior AI engineers.

Design, develop, deploy, and optimize large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and multi-model orchestration. Lead cost-performance governance, technical design reviews, AI engineering standards, and long-term platform strategy. Apply state-of-the-art optimization techniques to improve model scalability, latency, throughput, hardware utilization, and cost. Mentor senior technical leaders and collaborate with engineers, scientists, product managers, and program managers.

Leads a small data science team and cross-functional initiatives transforming bank claims management through machine learning and agentic workflows. Responsibilities include data exploration, model development, evaluation, validation, deployment, roadmap development, stakeholder influence, and establishing datasets, tools, and evaluation protocols for enterprise AI. The role remains hands-on while providing strategic oversight and developing team talent.

Leads data science initiatives for commercial banking by developing and validating machine learning models, conducting statistical analysis and back-testing, modernizing data infrastructure, and building analytical tools for risk, underwriting, portfolio management, and client-focused products.

Build and deploy machine learning and statistical models across the credit card lifecycle, including marketing, acquisitions, underwriting, and fraud prevention. Partner with data scientists, software engineers, and product managers; analyze large-scale numeric and textual datasets; conduct model design, training, evaluation, validation, and implementation; and translate complex analyses into business outcomes.

Leads data science initiatives for US Card acquisitions, developing and deploying machine learning models across their full lifecycle. Partners with data scientists, software engineers, product managers, and business stakeholders to solve complex problems, analyze large-scale numeric and textual datasets, validate models, and translate technical findings into business outcomes. The role also involves team leadership, talent development, model governance, monitoring, and ongoing model improvements.

Leads data science initiatives for Capital One’s Card Mainstreet business. Partners with data scientists, software engineers, and product managers to develop customer-focused solutions; analyzes large-scale numeric and textual data; builds, validates, and implements machine learning models; translates technical findings into business outcomes; and supports innovation and team talent development.

Paid 12-week applied research internship for current PhD students. Interns will develop and evaluate AI and machine learning solutions, collaborate with researchers, engineers, data scientists, and product managers, use technologies such as PyTorch and AWS, and contribute to production systems or academic publications. Research areas include foundation models, LLMs, reinforcement learning, causal inference, recommendation systems, interpretability, and agentic systems.

Twelve-week, full-time AI Engineering internship focused on building agentic AI applications and scalable AI infrastructure. Interns will prototype and productionize multimodal search, document processing, autonomous workflows, model training and inference optimization, guardrails, and evaluation frameworks. The role involves collaboration with research scientists, product managers, and engineers while using technologies such as PyTorch, AWS Ultraclusters, and agentic frameworks. Applicants must be current master's students continuing their degree program.

Twelve-week paid PhD internship focused on researching, prototyping, and productionizing AI systems and agentic workflows. Interns will build multimodal search, document-processing, autonomous-agent, training, inference, guardrail, and evaluation capabilities. The role involves collaborating with research scientists, product managers, and engineers while using cloud infrastructure, PyTorch, and agentic frameworks to deliver scalable AI products.