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

The Advanced Data Science Manager leads a team of data scientists, develops data science strategies, manages client projects, and drives business development while providing thought leadership and mentoring.

Lead AI strategy and client engagements for life sciences clients, drive AI and cloud data strategy, manage and mentor consulting teams, engage C-suite stakeholders, oversee risk and delivery, and build AI-capable practices across the firm.

The Enterprise Architect will design scalable AI solutions, mentor teams, support business development, and manage client relationships while evolving technology practices.

Lead end-to-end delivery of custom technology solutions across supply chain functions (planning, manufacturing, warehouse, logistics, merchandising). Define architectures and roadmaps, identify agentic AI use cases, guide development/testing/deployment, lead cross-functional teams, manage scope/timelines/budgets, and run client workshops to translate technical solutions into business outcomes.

Develop advanced algorithms, apply machine learning, collaborate with clients, and assess new datasets and technologies for data science projects.

As an Advanced Data Science Consultant, you will develop algorithms, utilize machine learning techniques, collaborate with clients, and mentor junior team members to deliver advanced analytics solutions.

Lead AI partnership strategy and execution to grow AI Frontier Labs alliances. Own alliance performance, co-sell pipeline, joint GTM and solution development, partner account mapping, enablement, marketing, and executive alignment to scale generative AI adoption and revenue.

Lead ZAIDYN's AI Engineering function to design, build, and ship an enterprise-grade agentic AI platform. Own architecture, integrations (AWS Bedrock/AgentCore), LLMOps/eval frameworks, observability, governance, and team hiring/operations. Ensure production readiness, cost/latency controls, auditability, and cross-functional delivery with product and QA while representing the platform externally.

Lead architecture, design, and delivery of GenAI-enabled, large-scale distributed systems across frontend, APIs, services, data, and AI layers. Define standards, guide technical reviews, ensure production readiness, partner with cross-functional teams, and mentor engineers to drive scalable, reliable, and maintainable platform solutions.