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

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Lead architecture, cost-performance governance, AI standards, and design reviews while mentoring senior technical staff. Partner with research, engineering, product, and program teams to establish foundational AI roadmaps and deliver scalable, responsible systems.

Conduct applied AI research and build foundation models through design, training, evaluation, validation, and implementation. Collaborate with data scientists, engineers, and product managers to deliver scalable AI products. Research LLM pretraining, fine-tuning, reinforcement learning, robustness, explainability, and behavioral models. Develop platform or solution-level code, reproduce research, document experiments, and contribute to technical reports or conference submissions.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, agentic workflows, vector search, model evaluation, governance, and observability. Optimizes large-scale AI systems for cost, latency, throughput, scalability, and hardware utilization. Leads architecture and design reviews, establishes AI engineering standards, drives technical roadmaps, and mentors senior AI engineers.

Design, develop, optimize, deploy, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead optimization of production AI systems for scalability, latency, throughput, hardware utilization, and cost. Architect multi-model orchestration pipelines, establish governance standards, lead design reviews, contribute to technical roadmaps, and mentor senior AI engineering staff.

Design, develop, deploy, and support foundational AI systems, including LLM training and inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, reliability, and hardware utilization. Own complex system architecture, define AI service-level objectives, lead technical reviews, ensure security and compliance, contribute to long-term roadmaps, and mentor engineering staff.

Conduct applied research in AI foundations, large language models, and agentic AI. Build and evaluate foundation models, optimize training and inference, develop scalable machine learning solutions, and translate research into production systems. Lead cross-functional research initiatives with data scientists, engineers, and product managers while independently pursuing impactful research agendas. The role emphasizes deep learning, NLP, model fine-tuning, robustness, explainability, and deployment at scale.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, foundation model training, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimizes AI systems for cost, latency, throughput, scalability, and hardware utilization. Owns complex AI architecture, defines reliability objectives, leads technical reviews, ensures security and compliance, contributes to long-term technical roadmaps, and mentors senior and principal engineers.

Develop and deploy large-scale machine learning and personalization models for web and mobile customer experiences. Partner with data scientists, engineers, and product managers; analyze massive numeric and textual datasets; and manage model design, training, evaluation, validation, and implementation. Research advanced methods including foundation models, reinforcement learning, causal inference, transformer architectures, and recommender systems while translating technical findings into business outcomes.

Conduct applied research in AI foundations, large language models, and agentic AI. Build and evaluate foundation models, optimize training and inference, develop scalable AI solutions, and translate research into production systems. Lead cross-functional research initiatives with data scientists, software engineers, ML engineers, and product managers while pursuing impactful research and mentoring junior team members.

Develop and deploy high-scale machine learning and personalization models for Capital One’s web and mobile experiences. Responsibilities include researching recommendation systems, foundation models, reinforcement learning, causal inference, and transformer architectures; analyzing large datasets; building models through training, evaluation, validation, and implementation; and collaborating with data scientists, engineers, and product managers.