Principal Associate, Data Scientist - LLM Customization Team

At Capital One, we think big and do big things. We are not just a nationally recognized credit card issuer, a top 10 bank by deposit, but a high-tech company with products that 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.

AI Foundations LLM Customization team is at the center of bringing our vision for LLMs and GenAI at Capital One to life. Our work touches every aspect of the research life cycle, from research to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.

You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.

- Partner with a cross-functional team of data scientists, applied researchers, 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, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data.

- Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business specific applications and features.

- Build NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems.

- Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

- 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.

- Technical. You're comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.

- Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.

- You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.

- You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.

Qualifications: 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 (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics

- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics

- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

- Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)

- Experience with Large Language Models (LLM), Finetuning, and Deep Learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

New York, NY: $176,500 - $201,400 for Princ Associate, Data Science