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

The US Product Lead is responsible for the AI product roadmap, leading a team, driving outcomes, managing budgets, and coordinating cross-functional collaborations to enhance commercial performance through AI-driven solutions.

Lead end-to-end realization of AI strategy into production-grade, scalable solutions and platforms. Provide hands-on technical leadership, architect and implement integrated AI systems, manage engineers/contractors/vendors, enforce engineering quality/security standards, and translate business problems into high-impact technical outcomes in regulated enterprise environments.

Lead enterprise-wide applied AI strategy, system-level architecture, and operating-model design. Direct mixed teams (engineers, contractors, vendors), set governance/standards, and stay hands-on for architecture and code review. Ensure AI investments deliver measurable business outcomes, reusable capabilities, and coherent, secure solutions at scale.

Lead design, development, and deployment of enterprise AI agents and multi-agent systems. Architect scalable, secure AI/data systems, integrate vector DBs, embeddings, RAG, and cloud MLOps, drive automation/APIs, mentor engineers, set KPIs, and ensure observability, ethical AI, and production readiness.

The role involves designing and deploying AI systems for vaccine discovery, leading predictive modeling, integrating datasets, and mentoring colleagues on AI applications in vaccinology.

The PharmSci Agentic & Generative AI Architect designs and scales AI solutions for Pharmaceutical Sciences, ensuring production-readiness and effective integration with existing platforms. Responsibilities include architectural design, leading pilots, and implementing responsible AI frameworks while mentoring team members.

The Pharmacometrician & Systems Pharmacologist role involves developing quantitative models for drug discovery and clinical development, focusing on pharmacometrics, systems pharmacology, and model-informed drug development, while collaborating with multidisciplinary teams.

The Director of AI Engineering leads AI transformation in Vaccine R&D Operations by designing solutions for process automation, decision support, and model governance. Responsibilities include developing predictive models, optimizing workflows, and building production-grade AI platforms while collaborating across teams.

The role involves building AI-enabled solutions, developing data pipelines, and collaborating with teams to enhance Oncology R&D workflows.

Responsible for designing and developing AI solutions for Oncology R&D, collaborating with scientists to translate complex questions into actionable insights, and contributing technical expertise in rapidly prototyping AI applications.