Staff Applied Researcher

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: San Francisco, CAMcLean, VACambridge, MASan Jose, CANew York, NY
Salary: $306,300–$349,500 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k

This role $328k

$135k $372k

below market most similar roles pay here above market

This role pays more than 98% of similar roles. Most pay $183,250–$238,687 — the blue band above. At the midpoint, this role pays about $328k versus about $211k 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 1891 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1020 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Staff Applied Researcher

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The Staff Applied Researcher joins the AI Foundations team to drive strategic direction and mentor applied scientists as an individual contributor leader. You will partner with cross-functional teams of data scientists, software engineers, and product managers to deliver AI-powered products that transform how customers interact with their money. Day-to-day responsibilities include building AI foundation models through all development phases, including design, training, evaluation, and implementation. You will leverage a technical stack featuring Pytorch, AWS Ultraclusters, Huggingface, and Lightning to extract insights from massive numeric and textual datasets. The role focuses on pushing state-of-the-art AI developments into production, solving complex problems in training optimization, self-supervised learning, and robustness to create scalable, high-performance infrastructure for real-time, intelligent, and automated customer experiences.

Skills

Pytorch AWS Huggingface Lightning deep speed NeMo NLP LLM RLHF Graph Neural Networks Quantization Model Compression Supervised Finetuning Instruction-Tuning

What you'll do

Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Partner with cross-functional teams to deliver AI-powered products for customer banking experiences.
Leverage technologies like PyTorch, AWS Ultraclusters, and Huggingface to extract insights from large datasets.
Translate complex research findings into tangible business goals for stakeholders.
Define and steward novel research directions to expand the organization’s long-term scientific agenda.
Guide and mentor a team of applied scientists and their managers as an individual contributor.
Represent the company in the research community by collaborating with prominent academic faculty.
Stay current on state-of-the-art AI methods and seek opportunities to apply them to business problems.

What we're looking for

PhD in a relevant field plus 4 years of experience in Applied Research.
M.S. in a relevant field plus 6 years of experience in Applied Research.
Hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
Deep understanding of AI methodology foundations and experience building large deep learning models for language, images, events, or graphs.
Expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
Track record of delivering models at scale and experience delivering libraries or platform-level code to existing products.
Ability to own a research agenda and autonomously carry out long-running projects.
Experience with common training optimization frameworks like DeepSpeed or NeMo (preferred).

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