Applied Researcher I, AI Foundations

Capital One Financial

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: New York, NYMcLean, VACambridge, MASan Jose, CA
Salary: $218,700–$249,600 / yr
Posted: 49 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 $215k

This role $234k

$163k most similar roles pay here $290k

This role pays more than 57% of similar roles. Most pay $175,000–$254,750 — the shaded band above. At the midpoint, this role pays about $234k versus about $215k 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

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As an Applied Researcher I (AI Foundations), you will join the AI Foundations team to develop trustworthy and reliable AI systems for banking applications. You will collaborate with a cross-functional team of data scientists, software engineers, and product managers to build AI-powered products that transform how customers interact with their money. Your daily responsibilities include building AI foundation models through all phases of development—including design, training, evaluation, validation, and implementation—while translating complex research into tangible business goals. You will utilize a technical stack featuring PyTorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs to extract insights from large volumes of numeric and textual data. The role focuses on high-impact applied research, specifically addressing the challenge of integrating state-of-the-art AI developments into production systems to improve customer experiences through advanced machine learning models.

Skills

Pytorch AWS Huggingface Lightning VectorDBs LLM NLP Deep Learning RLHF Quantization Model Sparsification Training Parallelism Supervised Finetuning Instruction-Tuning Compiler Design Self-Supervised Learning

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, Hugging Face, and VectorDBs to extract insights from large datasets.
Develop scalable deep learning models for language, images, events, or graphs using open-source tools and cloud platforms.
Translate complex technical research into tangible business goals and actionable products for stakeholders.
Identify and solve large, undefined problems by researching and evaluating emerging technologies and methodologies.
Own and pursue a research agenda by selecting impactful problems and autonomously managing long-running projects.

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 own a research agenda and autonomously carry out long-running projects.

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