Top AI Jobs in NYC, NY

Design and implement Generative AI solutions, develop production-grade code, and collaborate with cross-functional teams to drive analytics initiatives and enhance decision-making.

As an AI Research Engineer, you will develop systems for research ideas, build datasets, implement models, and collaborate on AI capabilities with various teams.

Develop AI-assisted tools for Datadog developers, focusing on generating tests, fixing bugs, and improving performance with LLM integration.

AI Strategists drive the strategic deployment of Hebbia's platform within financial institutions, transforming workflows, creating value, and expanding commercial strategy.

The AI Growth Product Manager will strategize and grow AI agents at CoreWeave, collaborating with various teams to enhance business operations through AI integration and development.

The Lead AI/DevOps Engineer will lead DevOps initiatives, design AI infrastructure, develop solutions for AI use cases, and optimize cloud resources. They will collaborate with customers, security teams, and infrastructure teams to deliver effective AI solutions.

The Lead AI/DevOps Engineer will design, deploy, and manage AI infrastructure, lead DevOps initiatives, and optimize cloud resources while ensuring compliance with security standards.

Lead a team to deliver AI powered products, leveraging machine learning and NLP for customer applications, while collaborating with cross-functional teams.

The Senior Lead AI Engineer will develop AI components, collaborate with cross-functional teams, and optimize performance for large scale production AI systems.

Lead the design, development, and implementation of Generative AI applications, ensuring high performance and scalability in cloud-native environments. Collaborate with AI/ML teams to drive innovation and apply best practices in machine learning engineering.

Lead and scale Capcos Cyber + AI practice: define strategy and offerings, win and deliver complex cybersecurity and AI-enabled security programs, manage client relationships, drive pursuits and revenue, and mentor and grow teams.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

As an Applied Researcher I, you'll partner with cross-functional teams to deliver AI-powered products, build foundation models, and engage in applied research on advanced AI techniques.

Lead cross-functional teams to develop and deploy AI-powered products, improve AI system performance, and create innovative AI solutions at Capital One.

As a Technical Consultant, you will ensure client success by providing technical expertise for AI implementations, integrating monday.com into enterprise environments, and leading technical discussions with stakeholders.

The Lead AI Engineer will develop AI software components, partner with cross-functional teams, and optimize large-scale AI systems at Capital One.

Lead AI Engineer responsible for developing AI-powered products and deploying scalable AI solutions using technologies like LLM and machine learning algorithms. Collaborate with cross-functional teams to optimize performance and support AI systems.

The Data Scientist will collaborate with teams to develop AI features, build ML models, and translate complex data insights into business goals, leveraging technologies like Python and AWS.

As a Senior Lead AI Engineer, you will design and deploy AI software components, innovate LLM optimization techniques, and collaborate with cross-functional teams to enhance banking experiences at Capital One.

Lead Capital One's long-term vision for AI in Experience Design, drive AI tooling and training adoption, partner with executives to align product and design strategy, and scale AI-driven design processes, tooling, and operating models across the organization.

Lead multiple engineering and applied science teams to define technical vision, ship end-to-end AI/ML products, and ensure operational excellence. Drive model training, data pipelines, evaluation, deployment, and production operations while partnering with Product, hiring and developing talent, and building quality and evaluation practices for AI systems.

Lead design, development, deployment, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI performance (cost, latency, throughput), partner cross-functionally, and contribute to technical vision and roadmap.

Own AI features end-to-end from ideation to production for partner brands. Build evaluation, regression, and monitoring systems; embed with customers; codify playbooks and reliability infrastructure to safely ship GenAI/agentic systems at scale in a regulated environment.

Work on operational problems across launch, QA, monitoring, and approvals to design and deploy AI-enabled automations and internal tools that increase speed and quality. Measure impact, iterate quickly, and partner with cross-functional teams to remove bottlenecks and scale operational efficiency.

Lead design and deployment of AI-powered identity platforms, architect agentic ecosystems and RAG pipelines, ensure reliability and scalability of data infrastructure, mentor engineers, and integrate AI systems with enterprise data tools like Spark and Dagster.