Applied Researcher 5

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Salary
$262,500–$299,600 / yr
Employment
Full-time
Posted
10 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 $228k
This role $281k
$198k $311k
below market most similar roles pay here above market

This role pays more than 87% of similar roles. Most pay $208,675–$246,706 — the blue band above. At the midpoint, this role pays about $281k versus about $228k 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 2276 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1147 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Applied Researcher 5

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The Applied Researcher 5 joins the AI Foundations team to develop trustworthy and reliable artificial intelligence systems for banking. This role involves partnering with cross-functional teams of data scientists, software engineers, and product managers to build AI-powered products that transform how customers interact with their money. You will build AI foundation models through all phases of development, including design, training, evaluation, validation, and implementation. Key responsibilities include leading research threads that bridge prototype development with production deployment. You will utilize a technology stack including Pytorch, AWS Ultraclusters, Huggingface, and Lightning to analyze large volumes of numeric and textual data. The work focuses on applying state-of-the-art AI methodologies, such as self-supervised learning and RLHF, to solve complex business problems and create scalable, high-performance AI infrastructure.

Skills

Pytorch AWS Huggingface Lightning Deep Learning LLMs Graph Neural Networks RLHF Quantization Model Compression Supervised Finetuning Instruction-Tuning Transfer Learning Tokenization

What you'll do

  • Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
  • Leverage technologies like Pytorch, AWS Ultraclusters, and Huggingface to extract insights from large numeric and textual datasets.
  • Lead cross-functional research threads to bridge prototype model development with production deployment.
  • Translate complex technical research into tangible business goals for stakeholders and product managers.
  • Conduct high-impact applied research to integrate the latest AI developments into next-generation customer experiences.
  • Own and pursue a research agenda by identifying impactful problems and autonomously carrying out long-running projects.
  • Deliver libraries, platform-level code, or solution-level code to existing products at scale.

What we're looking for

  • Must have a PhD in a related field with 2 years of applied research experience or an MS with 4 years of experience.
  • Must have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Must have a deep understanding of AI methodology foundations and experience building large deep learning models.
  • Must have expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
  • Must have an engineering mindset with a track record of delivering models at scale for training and inference.
  • Must have experience delivering libraries, platform-level code, or solution-level code to existing products.
  • Must have a track record of high-quality machine learning ideas, such as first-author publications or projects.
  • Must possess the ability to autonomously own and pursue a research agenda and choose impactful research problems.

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