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

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Leads the design, development, deployment, and optimization of scalable AI and generative AI solutions. Translates business needs into secure, production-ready architectures; applies foundation models, NLP, retrieval, vector search, and agentic workflows; and implements MLOps and LLMOps practices. Manages project workstreams, evaluates solution performance, ensures security and compliance, collaborates with stakeholders, and coaches junior team members.

Lead design and delivery of scalable AI/ML systems: data wrangling, model training, deployment, and infrastructure. Manage teams, mentor staff, own project planning/budgeting, and collaborate with stakeholders to drive AI-driven business insights.

Lead and manage a software engineering team to design, build, test, and deploy AI-enabled applications (LLM integrations, RAG, APIs). Own project planning, budgeting, CI/CD, code quality, observability, microservices, and cross-functional collaboration while coaching and developing team members.

Lead and manage data science teams to build ML and deep learning models, maintain data pipelines and lakes, ensure data quality, deliver actionable insights, and manage project timelines and client expectations.

Lead and manage data and analytics initiatives for M&A and transactions, directing teams to build ML models, dashboards, and integrated data solutions using analytics and visualization tools, ensuring data quality, stakeholder alignment, and actionable insights to drive deal decisions.

Leads fraud and risk-focused data science initiatives, using Python and advanced analytics to generate strategic insights and improve business performance. Manages client engagements, data pipelines, project execution, and teams while mentoring staff and resolving stakeholder issues. Responsibilities include building data architectures, developing visualizations, improving processes, and maintaining professional, technical, and independence standards.

Design and implement AI-enabled integration solutions, cloud architectures, and enterprise technology platforms. Lead strategic planning, analyze business requirements, conduct feasibility studies, coach teams, manage stakeholders, and validate solutions with clients. Apply generative and agentic AI, IoT, sensor data, systems thinking, and enterprise architecture practices to solve complex business problems and drive innovation.

Design, build, and deploy scalable AI/ML systems: data ingestion, model development (Python, TensorFlow), NLP, software integration (C++, Java), data pipeline management, client collaboration, and mentoring junior team members.