Applied Researcher 4

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NYMcLean, VACambridge, MASan Jose, CA
Salary
$218,700–$249,600 / yr
Employment
Full-time
Posted
12 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 $202k
This role $234k
$185k $257k
below market most similar roles pay here above market

This role pays more than 92% of similar roles. Most pay $192,050–$211,200 — the blue band above. At the midpoint, this role pays about $234k versus about $202k 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 · Applied Researcher 4

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The Applied Researcher 4 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. The work requires leveraging a broad technology stack including Pytorch, AWS Ultraclusters, Huggingface, and Lightning to extract insights from large volumes of numeric and textual data. Key responsibilities include conducting high-impact applied research, translating complex technical findings into business goals, and collaborating on internal tech reports or conference submissions. You will solve problems related to training optimization, self-supervised learning, robustness, explainability, and RLHF.

Skills

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

What you'll do

  • Build AI foundation models through all phases of development including design, training, evaluation, and validation.
  • Leverage technologies like Pytorch, AWS Ultraclusters, and Huggingface to extract insights from large numeric and textual datasets.
  • Conduct high-impact applied research to integrate the latest AI developments into next-generation customer experiences.
  • Deliver AI-powered products by partnering with cross-functional teams of data scientists, software engineers, and product managers.
  • Translate complex technical research into tangible business goals for stakeholders.
  • Prepare internal technical reports or conference submissions summarizing novel methods and research findings.
  • Own and pursue a research agenda by identifying impactful problems and autonomously carrying out long-running projects.

What we're looking for

  • Currently has, or is in the process of obtaining, a PhD in a relevant field or an M.S. plus 2 years of experience in Applied Research.
  • Have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Possess a deep understanding of the foundations of AI methodologies.
  • Have experience building large deep learning models for language, images, events, or graphs.
  • Possess expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, or RLHF.
  • Demonstrate an engineering mindset with a track record of delivering models at scale for training data and inference volumes.
  • Have experience delivering libraries, platform-level code, or solution-level code to existing products.
  • Possess the ability to own and pursue a research agenda, including choosing impactful problems and autonomously carrying out long-running projects.

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