Applied Researcher IV

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Jose, CASan Francisco, CAMcLean, VACambridge, MANew York, NY
Salary
$218,700–$249,600 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $211k
This role $234k
$151k most similar roles pay here $269k

This role pays more than 65% of similar roles. Most pay $167,500–$254,750 — the shaded band above. At the midpoint, this role pays about $234k 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 878 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 872 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Applied Researcher IV

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As an Applied Researcher 4 on the AI Foundations team, you will collaborate with cross-functional teams of data scientists, software engineers, and product managers to develop AI-powered products for banking services. You will be responsible for building AI foundation models through every phase of development, including design, training, evaluation, validation, and implementation. Your daily work involves uncovering insights within massive volumes of numeric and textual data to improve customer experiences. To achieve these goals, you will utilize a technical stack featuring PyTorch, AWS Ultraclusters, Huggingface, and Lightning. The role requires expertise in large deep learning models, training optimization, self-supervised learning, and RLHF. You will also contribute to the research lifecycle by preparing internal tech reports or conference submissions regarding novel methods while translating complex technical findings into tangible business goals for the organization.

Skills

Pytorch AWS Huggingface Lightning LLM NLP Graph Neural Networks RLHF Self-Supervised Learning Quantization Model Compression Training Parallelism Instruction-Tuning pytorch-geometric DGL Cloud Computing

What you'll do

  • Develop AI foundation models through all phases of development including design, training, evaluation, and implementation.
  • Translate complex technical research into tangible business goals for stakeholders and product managers.
  • Conduct high-impact applied research to integrate state-of-the-art AI developments into customer experiences.
  • Analyze large volumes of numeric and textual data using tools like PyTorch, Hugging Face, and AWS.
  • Prepare internal technical reports or conference submissions summarizing novel methods and findings.
  • Identify and solve complex, undefined problems by researching and evaluating emerging technologies.
  • Deliver scalable models and production-level code for high-volume training and inference.

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 field plus 2 years of experience in Applied Research.
  • Experience building large deep learning models for language, images, events, or graphs is required.
  • Expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF is required.
  • Must have an engineering mindset with a track record of delivering models at scale for both training and inference.
  • Experience delivering libraries, platform-level code, or solution-level code to existing products is required.
  • Ability to own a research agenda and independently carry out long-running projects is required.
  • Preferred qualifications include specific expertise in LLM pre-training, graph neural networks, model optimization, or fine-tuning.

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