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

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.

The role involves designing, building, and maintaining an MLOps platform, developing workflows for ML applications, and integrating various technologies while supporting agile teams.

The Senior Associate - Data Scientist will develop AI and machine learning solutions, focusing on model lifecycle management and delivering AI initiatives in collaboration with business teams.

Design, build, and operationalize ML and Generative AI solutions (including LLMs, RAG, and agentic AI) across the model lifecycle. Collaborate with data, engineering, and product teams to deploy scalable models on cloud platforms, implement MLOps/CI-CD, create APIs and lightweight UI prototypes, and ensure governance, monitoring, and responsible AI practices.

Lead AI model development and deployment to solve business problems: translate requirements into AI use cases, prototype and fine-tune LLMs, build data pipelines, integrate models into enterprise platforms, collaborate with engineering and product teams, and create visualizations and documentation for stakeholders.

Contribute to enterprise AI initiatives by developing, validating, and operationalizing ML and generative/agentic AI solutions. Work across the model lifecycle (data exploration, feature engineering, training, deployment, monitoring) using AWS, Snowflake, and Databricks; implement LLM/RAG approaches, APIs, lightweight UI prototypes, and adhere to responsible AI, governance, and MLOps practices.

As an AI Product Insights Analyst, you'll develop AI-enabled analytics frameworks, manage data models, and collaborate to enhance decision-making through Generative AI applications.

The role involves model validation, monitoring AI model performance, challenging model developers, and translating technical requirements into practical evaluations and controls for AI and ML models.