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

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

Lead design, build, and productionize scalable ML models and pipelines. Collaborate with product and data science teams, implement cloud-based architectures, ensure CI/CD, monitoring, model governance, and responsible AI practices.

As a Lead AI Engineer, you will design, develop, and support AI software components while partnering with cross-functional teams to deliver AI-powered products at Capital One.

The Senior Lead AI Engineer will develop and support AI components, lead a cross-functional team, and drive innovation in AI systems at Capital One.

The role involves building machine learning models, collaborating with teams, and leveraging technology to analyze data, ultimately enhancing credit underwriting for business cards.

Lead development of production machine learning models for co-branded card decisioning. Partner with cross-functional teams, use Python, Spark, H2O, and AWS to design, train, validate, and deploy models for approve/decline, product optimization, and customer valuation.

Lead design, develop, deploy, and support foundational AI systems (LLM training/inference, similarity search, guardrails, observability). Partner cross-functionally to optimize scalability, cost, latency, and throughput, apply state-of-the-art research to production, and shape long-term AI platform roadmap.

Lead an AI engineering team to design, build, deploy, and optimize large-scale generative AI systems. Oversee foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and make strategic build-vs-buy decisions. Drive technical vision, roadmap, and talent development while ensuring scalable, cost-efficient, and responsible AI production systems.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.