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

Leads the design, development, and operation of enterprise AI and machine learning platforms across public and private clouds. Builds MLOps infrastructure, model deployment and inference services, observability, governance, automation, and data workflows. Troubleshoots complex platform issues, improves reliability and scalability, influences architecture, partners with cross-functional teams, evaluates emerging AI technologies, and mentors engineers.

Leads the design, development, and operation of enterprise AI platforms across public and private clouds. Responsibilities include MLOps, model deployment and inference, infrastructure automation, observability, monitoring, governance, reliability, incident response, and platform scalability. The role provides technical leadership, mentors engineers, influences architecture, supports AI adoption, and partners with security, infrastructure, risk, and governance teams to deliver secure and resilient machine learning and generative AI capabilities.

Leads Mastercard’s enterprise AI and data strategy, including responsible AI frameworks, governance, risk assessment, regulatory monitoring, and integration of generative and agentic AI. Partners with legal, privacy, compliance, risk, technology, product, and business teams to establish guardrails, translate emerging developments into strategic guidance, improve AI literacy, and mentor practitioners.

Leads Mastercard’s Open Finance data science strategy and global organization. Oversees production-grade AI and machine learning solutions for transaction categorization, entity extraction, fraud detection, credit risk, propensity modeling, personalization, and financial insights. Partners with Product, Engineering, Sales, Risk, Marketing, Legal, and Compliance to commercialize scalable solutions, establish MLOps and governance practices, ensure responsible AI, and grow high-performing data science teams.

Architect and engineer secure, scalable enterprise AI infrastructure for LLM training and inference, machine learning, agentic AI, and production platforms. Lead HPC, GPU, Kubernetes, cloud, networking, storage, reliability, observability, security, and automation strategies. Resolve complex performance and scalability challenges, establish engineering standards, evaluate emerging technologies, lead cross-functional initiatives, and mentor engineers in a regulated environment.

Leads the architecture and engineering of secure, scalable enterprise AI infrastructure. Designs platforms for LLM training and inference, machine learning, agentic AI, and production workloads using HPC, GPUs, Kubernetes, hybrid cloud, networking, storage, and automation. Establishes standards for reliability, security, observability, governance, and compliance; resolves complex performance challenges; evaluates emerging technologies; leads cross-functional initiatives; and mentors engineers.

Leads Mastercard’s Open Finance data science strategy, products, and global organization. Oversees production machine learning and AI capabilities for transaction categorization, entity extraction, fraud detection, credit risk, personalization, and predictive analytics. Partners with Product, Engineering, Sales, Risk, Marketing, Legal, and Compliance to commercialize scalable, explainable, and responsibly governed solutions. Builds talent, establishes operating standards, drives MLOps and model governance, and advises executives and customers on AI applications.

Leads Mastercard’s global AI Engineering organization within the AI Center of Excellence. Oversees end-to-end delivery and scaling of enterprise AI products, agentic AI solutions, reusable AI capabilities, and intelligent automation. Partners across engineering, infrastructure, data, security, risk, architecture, product, and business teams to ensure secure, reliable, governed, production-ready solutions. Drives adoption, measurable business outcomes, operational excellence, and responsible AI practices while developing global engineering leaders and teams.

Leads Mastercard’s global AI Engineering organization, delivering enterprise AI products, agentic AI solutions, reusable AI capabilities, and intelligent automation from design through production. Oversees engineering execution, production readiness, security, governance, resiliency, observability, and measurable business outcomes. Partners across platform, infrastructure, data, security, risk, architecture, product, and business teams while building a high-performing global organization of AI leaders, architects, and engineers.

Leads AI engineering strategy and execution across Mastercard, overseeing AI/ML architecture, deployment, monitoring, optimization, governance, and risk management. Partners with product, technology, data science, and business leaders to deliver scalable AI solutions and measurable business impact. Provides technical mentorship, establishes engineering standards, evaluates emerging technologies, and guides enterprise transformation through generative AI and machine learning.