Principal Data Scientist, AI Foundations
$162k - $185k • New York, NY • Full-time
Posted 12d ago
Job Location
New York, NY
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
LLM Engineer
About the job
As a Principal Data Scientist on the AI Foundations Specialist Models team, you will be instrumental in building and shipping state-of-the-art, scalable AI/ML solutions for Capital One's award-winning mobile app. You will partner with product, tech, and design teams to deliver dynamic and personalized customer experiences, including enabling interactions with Capital One's digital assistant and enhancing content search capabilities. This role is focused on experimenting with, innovating, and creating next-generation experiences powered by the latest emerging generative AI technologies, driving disruption at a massive scale across billions of customer records.
Responsibilities
- Partner with a cross-functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
- Leverage a broad stack of technologies including Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and VectorDBs to extract insights from large volumes of numeric and textual data.
- Act as an expert in Natural Language Processing (NLP) to harness, adapt, and fine-tune Large Language Models (LLMs) for customer-facing applications.
- Build machine learning and NLP models through all development phases: design, training, evaluation, and validation.
- Collaborate with engineering teams to operationalize models in scalable and resilient production systems serving over 80 million customers.
- Translate complex technical work into tangible business goals and communicate findings effectively to non-technical audiences.
Requirements
- Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 5 years of data analytics experience, OR Master's Degree in a quantitative field (or MBA with quantitative concentration) plus 3 years of data analytics experience, OR PhD in a quantitative field.
- Experience working with AWS.
- At least 3 years of experience in Python, Scala, or R.
- At least 3 years of experience with machine learning.
- At least 3 years of experience with SQL.
- Hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
- Experience in training language models or large computer vision models.
- Expertise in at least one key subdomain such as training optimization, self-supervised learning, explainability, or RLHF.
- Engineering mindset with a track record of delivering models at scale in both training data and inference volumes.
- Experience delivering libraries, platforms, or solution-level code to existing products.