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

Leads independent validation and governance of predictive, generative, and agentic AI models. Develops evaluation frameworks, benchmarks, testing protocols, monitoring, observability, and third-party validation practices. Translates regulatory and model-risk requirements into controls, standards, playbooks, and audit evidence. Presents findings to senior leaders and governance committees, mentors colleagues, and partners with data science, engineering, legal, compliance, cybersecurity, and risk teams.

Design, build, and deploy cloud-native, agentic AI applications on AWS/GCP. Apply AI and automation to improve developer productivity, design and consume APIs, ensure security and compliance, support generative/agentic AI in production, collaborate in Agile teams, and contribute to architecture and engineering best practices.

The Director will strategize and govern AI experiences for field personas, develop frameworks, conduct hands-on AI concept experimentation, and ensure alignment across stakeholders.

Lead design and delivery of full‑stack, cloud‑native AI and GenAI solutions; define AI strategies; architect secure, scalable platforms; mentor engineering teams; run pilots, integrate successful technologies, and partner across cloud, security, data, and business stakeholders to improve developer experience and drive enterprise adoption.

Design, build, and operate secure, compliant, scalable GCP cloud and AI platforms. Provide IaC (Terraform), GKE/container orchestration, Vertex AI/GenAI enablement, CI/CD and MLOps foundations, security and governance controls, observability, cost optimization, and cross-team collaboration to support AI workloads in a regulated financial environment.

Own end-to-end decision intelligence product domains: build, deploy, and monitor ML models and behavioral signals; lead experimentation and causal measurement; develop generative AI solutions and personalization; partner with product and engineering to define roadmaps and reusable ML platform assets that drive measurable business outcomes.

Lead design and build of New York Life's enterprise AI platform and agentic solutions. Work across cloud-native infrastructure, model and agent lifecycle, RAG knowledge systems, multi-agent orchestration, MLOps/LLMOps, governance, CI/CD, observability, and production operations. Partner with security, legal, and architecture to embed responsible AI and deliver production-ready, compliant AI systems.

Work on statistical and machine learning solutions and generative AI (LLMs) projects. Translate business questions into models, perform exploratory analysis, feature engineering, model validation, and communicate results to technical and non-technical stakeholders throughout an 11-week summer internship.

Develop, train, and deploy machine learning and generative AI models in production. Focus on engineering aspects: scalable software, MLOps/DevOps integration, CI/CD pipelines, monitoring (e.g., New Relic), and automation frameworks to ensure model reliability and performance.

Lead design and implementation of the enterprise AI platform, defining reference architectures, reusable patterns, and complex services (lifecycle registries, control plane, memory, model abstraction). Build agentic AI capabilities, ensure secure governed deployments, drive portability and engineering standards, review designs, mentor senior engineers, and deliver production-grade AI systems across cloud-native infrastructure.