Sr. Distinguished Applied Researcher

About the role

The role is responsible for driving strategic direction through collaboration with Applied Science, Engineering, and Product leaders across Capital One. The ideal candidate will guide and mentor a team of applied scientists and their managers without being a direct people leader.

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money.
• 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.
• 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.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Qualifications

• PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research.
• 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.
• A technical background with hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• A deep understanding of the foundations of AI methodologies.
• 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.
• 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.
• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.