PhD Applied Research Intern

Capital One Financial

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Hybrid

Quick summary

Work type: Hybrid
Location: New York, NYMcLean, VASan Jose, CA
Employment: Full-time
Posted: 49 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $166k

$100k $232k

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This listing doesn't post a salary. Most similar roles pay $112,697–$219,256.

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Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · PhD Applied Research Intern

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The Current PhD, Applied Research Internship Program - Summer 2027 places interns within the AI Foundations team to develop trustworthy and reliable AI systems. Participants will engage in high-impact applied research to solve large-scale problems, pushing the latest AI developments into next-generation customer experiences or contributing to academic publications. Day-to-day responsibilities include partnering with cross-functional teams of researchers, data scientists, and engineers to test and design AI-powered products. The role requires utilizing a broad technology stack including PyTorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs. Candidates must possess skills in deep learning theory, mathematics, and programming. The work focuses on domain-specific challenges such as Foundation Models, Reinforcement Learning, Causal Inference, Model Inference Optimization, and Interpretability to improve how customers interact with their money.

Skills

Python PyTorch AWS Huggingface Lightning VectorDBs Deep Learning Reinforcement Learning LLMs Causal Inference Model Inference Optimization Agentic AI Mixture of Experts PPO RLHF Foundation Models

What you'll do

Conduct high-impact applied research to translate latest AI developments into next-generation customer experiences.
Design and test AI-powered products to improve how customers interact with their financial data.
Use PyTorch, AWS Ultraclusters, Huggingface, and VectorDBs to analyze large volumes of numeric and textual data.
Translate complex technical research into tangible business goals for non-technical stakeholders.
Partner with leading researchers to author and publish papers at top academic conferences.
Solve large-scale, real-world problems by applying deep learning theory to production-level engineering.
Evaluate and research emerging technologies to identify opportunities for practical application in banking.

What we're looking for

Must be currently enrolled in an accredited PhD program.
Must complete the first year of PhD coursework by June 2027.
Must be located in the continental United States for in-person attendance.
Must have a PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field (preferred).
Must be in the 2nd or 3rd year of a PhD program (preferred).
Must have programming experience, such as Python, and experience with at least one deep learning framework like PyTorch (preferred).
Must have publications in leading conferences such as ICLR, NeurIPs, ICML, ACL, NAACL, EMNLP, KDD, or CVPR (preferred).
Must have a research focus in areas like Foundation Models, Reinforcement Learning, Causal Inference, or Recommendation Systems (preferred).