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

The role involves collaborating with teams to develop AI-powered products, leveraging NLP and LLM technologies while operationalizing models into production systems.

The Applied Researcher I will partner with teams to deliver AI products, leverage technologies to analyze data, and build foundation models. This role includes engaging in applied research and translating technical findings into business goals.

As a Lead AI Engineer, you will develop, deploy, and support AI software components, collaborate with cross-functional teams, and optimize performance of large-scale AI systems.

The Lead AI Engineer will design, develop, deploy, and support AI software components, collaborating with cross-functional teams to create scalable AI solutions that enhance customer interactions and operational efficiency.

In this role, you will develop AI foundation models, conduct applied research, and collaborate with cross-functional teams to enhance customer experiences through AI-powered products.

The Lead AI Engineer will develop and deploy AI software components, optimize AI systems, and collaborate with cross-functional teams at Capital One to enhance customer interactions through AI technology.

As a Senior Lead AI Engineer, you will design and develop advanced AI systems, collaborate with cross-functional teams, and introduce innovative AI techniques while mentoring others.

The Senior Lead AI Engineer will collaborate with cross-functional teams to design, develop, and implement AI software solutions, focusing on large-scale production systems and AI model optimization.

Lead model validation and risk quantification across business domains. Partner with data scientists, engineers, and PMs to build and challenge production models using Python, Spark, H2O, and cloud tools. Drive model governance, backtesting, and present identified model risks to executives while mentoring teams and advancing validation frameworks.

Design, develop, deploy, and support foundational AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize training/inference for scalability, cost, latency, and throughput. Partner cross-functionally to deliver production AI services and shape the technical vision and roadmap for foundational AI at scale.