Top AI & Machine Learning Jobs

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.

Build and optimize foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead multi-model orchestration, cost-performance optimization, technical standards, and design reviews for scalable production AI. Partner cross-functionally, contribute to long-term AI roadmaps, and mentor senior technical leaders while applying state-of-the-art research to responsible AI systems.

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.

Build and lead scalable generative AI platforms, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, and hardware utilization; architect multi-model orchestration pipelines; establish technical standards and governance; and mentor senior AI engineers while shaping the long-term platform roadmap.

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.

Build and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Design multi-model orchestration pipelines, improve model cost, latency, throughput, and scalability, establish AI governance standards, lead technical reviews, and mentor senior AI engineering staff. Collaborate with engineers, scientists, technical program managers, and product managers to deliver responsible AI capabilities.

Design, develop, deploy, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI platforms for cost, latency, throughput, scalability, and hardware utilization. Lead architecture and governance reviews, shape long-term platform roadmaps, establish engineering standards, and mentor senior AI engineers across the organization.

Build and optimize foundational AI systems, including LLM training and inference, agentic workflows, vector search, guardrails, evaluation, and observability. Partner with engineering, research, product, and program teams to deliver scalable AI products. Lead model and infrastructure optimization for cost, latency, throughput, and hardware utilization; establish governance and engineering standards; contribute to technical roadmaps; and mentor senior AI leaders.

Design, develop, deploy, and support foundational AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize distributed AI systems for cost, latency, throughput, scalability, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor engineering teams.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture, cost-performance optimization, technical standards, and roadmap development for scalable production AI platforms. Partner with researchers, engineers, technical program managers, and product managers while mentoring senior technical staff and advancing responsible AI practices.