Capital One aims to transform software development by leveraging state-of-the-art AI architectures to operate across billions of customer records and unlock opportunities to improve financial lives through data-driven decision-making.
Requirements
- Experience working with AWS
- Experience building production-grade agentic platforms, including RAG and graph-augmented systems, MCP or tool-calling integrations
- Demonstrated expertise in advanced model customization techniques—such as fine-tuning, parameter-efficient tuning (LoRA/QLoRA), reinforcement learning, or preference optimization
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
- Experience with open-source languages
- Experience with clustering, classification, sentiment analysis, time series, and deep learning
- Ability to retrieve, combine, and analyze data from a variety of sources and structures
Responsibilities
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
- Design, build, and deliver state-of-the-art, scalable AI architectures that transform how software is developed at Capital One
- Create multi-agent solutions across the software development lifecycle—including code generation, migration, troubleshooting, root-cause analysis, and documentation
- Leverage technologies such as LangGraph, MCP, agent-to-agent protocols, and advanced model customization techniques
Other
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics, or a Master's Degree in a quantitative field plus 3 years of experience performing data analytics, or a PhD in a quantitative field
- Master’s Degree in “STEM” field plus 3 years of experience in data analytics, or PhD in “STEM” field
- Prior research and publications in AI/ML conferences
- Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
