Applied Researcher I, AI Foundations, VLM

Capital One Financial

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
New York, NYSan Francisco, CAMcLean, VACambridge, MASan Jose, CA
Salary
$218,700–$249,600 / yr
Posted
9 days ago
Freshness
Confirmed live 2 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $230k
This role $234k
$172k most similar roles pay here $302k

This role pays less than 51% of similar roles. Most pay $202,800–$256,950 — the shaded band above. At the midpoint, this role pays about $234k versus about $230k for comparable roles.

Based on 240 similar postings.

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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Applied Researcher I, AI Foundations, VLM

Role Posting Log in to save

As an Applied Researcher I (AI Foundations, VLM) on the AI Foundations team, you will collaborate with a cross-functional group of data scientists, software engineers, and product managers to deliver AI-powered products for banking services. You will build AI foundation models through every phase of development, including design, training, evaluation, validation, and implementation. Your daily work involves leveraging a technical stack featuring Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs to extract insights from massive volumes of numeric and textual data. The role focuses on high-impact applied research to integrate state-of-the-art AI developments into next-generation customer experiences. You will solve complex problems involving large deep learning models for language, images, events, or graphs, utilizing specialized techniques such as training optimization, self-supervised learning, robustness, explainability, and RLHF to improve how customers interact with their money.

Skills

PyTorch AWS Huggingface Lightning VectorDBs LLM NLP Deep Learning RLHF Self-Supervised Learning Quantization Model Sparsification Training Optimization Machine Learning Cloud Computing Compiler Design

What you'll do

  • Build AI foundation models through all phases of development including design, training, evaluation, validation, and implementation.
  • Conduct high-impact applied research to integrate state-of-the-art AI developments into next-generation customer experiences.
  • Utilize a broad technology stack including PyTorch, AWS Ultraclusters, Hugging Face, and VectorDBs to analyze large datasets.
  • Translate complex technical research into tangible business goals for cross-functional stakeholders.
  • Develop scalable models and solutions for high volumes of training data and inference.
  • Research and evaluate emerging technologies while staying current on published state-of-the-art methods.
  • Own and pursue a research agenda by identifying impactful problems and executing long-running projects autonomously.

What we're looking for

  • Must have a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field.
  • Alternatively, must have an M.S. in a relevant technical field plus 2 years of experience in Applied Research.
  • Must have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Must possess a deep understanding of the foundations of AI methodologies.
  • Must have experience building large deep learning models for language, images, events, or graphs.
  • Must demonstrate an engineering mindset with a track record of delivering models at scale for training data and inference volumes.
  • Must have a track record of high-quality machine learning ideas, such as first author publications or significant projects.
  • Must be able to independently own and pursue a research agenda including selecting problems and managing long-running projects.

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