Principal Data Scientist, AI Foundations
About The Position
The AI Foundations Specialist Models Data Science team builds and ships scalable architecture and AI/ML solutions for Capital One’s mobile app. The team partners with product, technology, and design teams to create dynamic, personalized customer experiences, including features that support Capital One’s digital assistant Eno and content search. In this role, the Principal Data Scientist will experiment with and develop next-generation experiences using emerging generative AI technologies. The position partners with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products. It applies technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to large volumes of numeric and textual data. The role brings expertise in NLP and LLMs to adapt and fine-tune models for customer-facing applications, and develops machine learning and NLP models from design through training, evaluation, and validation. The scientist also works with engineering teams to operationalize models in scalable, resilient production systems serving more than 80 million customers, and communicates technical work in terms of business goals. The ideal candidate is customer-focused, innovative, creative, technically strong, influential, and a leader who develops talent and challenges conventional approaches. They have hands-on experience with LLMs, open-source tools, and cloud platforms, experience training language or large computer vision models, and expertise in a relevant subdomain such as training optimization, self-supervised learning, explainability, or RLHF. They bring an engineering mindset and a track record of delivering models at scale, as well as libraries, platforms, or solution-level code to existing products.
Requirements
- Currently has, or is obtaining by the scheduled start date, a bachelor's degree in a quantitative field plus 5 years of experience performing data analytics; or a master's degree in a quantitative field, or an MBA with a quantitative concentration, plus 3 years of experience performing data analytics; or a PhD in a quantitative field.
- Hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
- Experience training language models or large computer vision models.
- Expertise in one or more relevant subdomains, such as training optimization, self-supervised learning, explainability, or RLHF.
- An engineering mindset demonstrated by delivering models at scale in training data and inference volumes.
- Experience delivering libraries, platforms, or solution-level code to existing products.
- Ability to communicate clearly and effectively with non-technical audiences.
Nice To Haves
- Master’s degree or PhD in a STEM 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.
Responsibilities
- Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
- Use technologies including PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to uncover insights in large volumes of numeric and textual data.
- Apply NLP and LLM expertise to adapt and fine-tune models for customer-facing applications and features.
- Build machine learning and NLP models through design, training, evaluation, and validation.
- Partner with engineering teams to operationalize models in scalable and resilient production systems serving more than 80 million customers.
- Translate technical work and its complexity into tangible business goals.
- Research and evaluate emerging technologies and identify opportunities to apply state-of-the-art methods.
- Work with stakeholders to challenge conventional thinking and improve the status quo.
- Contribute to talent development within and beyond the team.
Benefits
- Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.
- Eligibility to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Ph.D. or professional degree
