At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Requirements
- Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
- An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
- Experience in delivering libraries, platform level code or solution level code to existing products.
- Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.
- PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series)
- Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems
- Experience with production real-time and streaming environments
Responsibilities
- Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
- Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
- Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
- Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
- Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money.
- Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
Other
- This is an individual contributor (IC) role driving strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One.
- As a well-respected IC leader, you will guide and mentor a team of applied scientists and their managers without being a direct people leader.
- You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community.
- You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
- A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
