Jobs at Capital One

Conduct applied AI research and build foundation models from design through training, evaluation, validation, and deployment. Partner with data scientists, engineers, and product managers to deliver scalable AI products. Lead research initiatives involving large deep learning models, optimization, self-supervised learning, robustness, explainability, and fine-tuning. Translate research into production systems, develop platform or solution-level code, and guide long-term research agendas with measurable customer and business impact.

Conduct applied research in AI safety and multimodal machine learning. Build and evaluate foundation models across design, training, validation, and deployment; develop safety guardrails and red-team multimodal systems; optimize large-scale training and inference; reproduce and extend peer-reviewed research; deliver libraries and platform code; and collaborate with engineering, product, and research teams on production AI applications.

Leads applied AI research and strategic direction for foundation models and large-scale machine learning systems. Responsibilities include designing, training, evaluating, validating, and deploying models; pursuing novel research; collaborating with engineering, product, and data science teams; mentoring scientists and managers; translating research into business outcomes; and representing the company in the research community. Focus areas may include LLMs, behavioral models, optimization, fine-tuning, data preparation, and scalable production AI.

Architect and modernize highly available card-account and transaction platforms, migrating monoliths to microservices and event-driven systems. Define technical vision, architecture, API standards, and engineering best practices while ensuring scalability, security, performance, and operability. Provide hands-on technical leadership, mentor engineers, lead cross-domain initiatives, conduct architectural reviews, and collaborate with engineering, product, and architecture leaders.

Develop and deploy scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize model performance, infrastructure utilization, latency, throughput, and cost. Own complex AI architecture, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to foundational AI roadmaps, and mentor engineering staff.

Conduct applied AI research and build foundation models across design, training, evaluation, validation, and deployment. Collaborate with data scientists, engineers, and product managers to deliver scalable AI products. Research emerging methods, optimize large deep learning models, develop platform or solution code, publish findings, and pursue an independent research agenda focused on impactful customer applications.

Design, develop, deploy, and support large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and model evaluation. Optimize AI systems for scalability, latency, throughput, hardware utilization, and cost. Define technical roadmaps and governance standards, lead design reviews, integrate heterogeneous AI systems, and mentor senior technical staff.

Lead AI Foundations data science work for Capital One’s mobile app, building and validating scalable ML and NLP models, including LLM-based solutions. Partner with product, engineering, and design teams to deliver personalized customer-facing AI features, operationalize models in production, and translate technical results into business impact.

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

Build, deploy, scale, and maintain machine learning models and platforms in production. Responsibilities include developing ML applications, distributed data pipelines, cloud-based infrastructure, model monitoring, retraining, CI/CD automation, testing, governance, and responsible AI practices. The role collaborates with Product, Data Science, and Agile engineering teams while optimizing algorithms and supporting large-scale containerized systems.

Conduct applied AI research and develop foundation models from design through training, evaluation, validation, and production deployment. Collaborate with data scientists, software and machine learning engineers, and product managers to deliver scalable AI products. Lead research initiatives spanning large-model training, optimization, fine-tuning, robustness, explainability, and reinforcement learning. Translate research findings into platform and product solutions while pursuing an independent research agenda and mentoring others.

Designs human-centered digital and physical product experiences for Capital One. Responsibilities include creating journey maps, service blueprints, high-fidelity designs, and prototypes; applying interaction, visual, and service design expertise; using research, data, technology constraints, and design systems; facilitating collaboration with product, technology, and business partners; and communicating design decisions to diverse audiences.

Leads enterprise AI/ML technical programs from strategy through production, including platform modernization, scalability, governance, and delivery. Owns executive communications, roadmap alignment, investment prioritization, architectural decisions, and program risk management. Establishes TPM practices and performance frameworks, mentors TPM leaders, and collaborates with researchers, engineers, business leaders, and cross-functional stakeholders to deliver reliable AI/ML capabilities.

Designs, develops, tests, and maintains complex Workday Finance integrations using web services and related technologies. Leads integrators and configurators, supports Finance modules, automates workflows, performs code reviews, improves business processes, and partners with product owners and stakeholders in an Agile environment.

Conduct applied research and develop AI foundation models, including vision-language model customization, across design, training, evaluation, validation, and deployment. Collaborate with data scientists, engineers, and product managers to deliver scalable AI products. Research emerging methods, reproduce and extend published work, document findings, contribute to technical reports or conference submissions, and independently pursue impactful research agendas.

Leads product strategy and operations for AI/ML platforms, including roadmap prioritization, operational frameworks, adoption of generative and agentic AI, and internal user experience improvements. Partners with Product, Engineering, TPM, and business teams to translate vision into execution, manage programs, develop teams, and drive strategic decisions through quantitative and qualitative analysis.

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

Leads project management and operations for a large design organization. Develops operational strategy, manages cross-functional design and program teams, oversees standards and practice management, and drives portfolio prioritization, resourcing, metrics, and complex initiatives. Partners with executive, product, technology, and design leaders to scale impact, improve processes, and operationalize human-centered programs. Requires substantial project and people management experience, with preferred expertise in design operations, design systems, SDLC/PDLC, and design tools.

Design, develop, deploy, and support foundational AI systems, including model training, LLM 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 architectures, define reliability objectives, ensure security and compliance, influence technical roadmaps, and mentor engineering teams.

Conduct applied AI research and lead development of foundation models from design through production deployment. Collaborate with data scientists, software and machine learning engineers, and product managers to deliver scalable AI products. Research advanced methods, optimize training and inference, evaluate model performance, and translate research into production impact. The role also involves owning research agendas, publishing or advancing machine learning methods, leading cross-functional initiatives, and mentoring junior researchers or engineers.