Senior Lead - Applied Research

Center 2 (19050), United States of America, McLean, Virginia

Senior Lead - Applied Research

At Capital One, we think big and do big things. We are a Top-10 bank by deposits—a high-tech company, scientific laboratory, and a nationally recognized brand. Our products reach tens of millions of consumers and have been recognized by numerous prestigious awards for their customer-friendliness. Capital One was the first major bank to move to cloud computing and to publish APIs for the Open Banking future. AI is transforming every industry, at Capital One you will help shape how it transforms financial services.

 

Team Description: 

The AI Foundations team partners with product, tech, and business leaders to advance and deliver on our strategic vision to harness emerging AI advances. This team will address fundamental invention challenges in AI for data (discovery, redaction, cleansing) and data for AI (fusing across sources, types, quality).  

In this role, you will: 

• 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.

The Ideal Candidate:

• Customer first. 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.

• 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.

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.

• Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing.

•  Has a deep understanding of the foundations of AI methodologies. 

• Experience building LLMs or large computer vision models as well as expertise in one or more key subdomain such as: 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 delivered libraries

• 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.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 2 years of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 3 years of experience in applied research

Preferred Qualifications:

• At least 2 years of experience with Deep Learning

• At least 2 years experience in developing and debugging in C/C++, Python, or C#

• At least 2 years of experience with LLM practices such as prompt engineering, supervised fine tuning, distillation

• Master’s Degree or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

• At least 2 years of experience in interdisciplinary research collaborations

• At least 2