Senior Manager, Data Science - LLM Customization Team

Capital One Capital One · Banking · New York, NY +2

Senior Manager of Data Science focused on LLM customization within Capital One's AI Foundations team. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch, Hugging Face, LangChain, and VectorDBs. Responsibilities include adapting and fine-tuning LLMs for business applications, building NLP models through development phases, and operationalizing them in production systems. The ideal candidate has experience in training language models, expertise in areas like self-supervised learning or RLHF, and a track record of delivering models at scale.

What you'd actually do

  1. Partner with a cross-functional team of data scientists, applied researchers, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
  2. Leverage a broad stack of technologies — Pytorch, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
  3. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business specific applications and features.
  4. Build NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems.

Skills

Required

  • Natural Language Processing (NLP)
  • Large Language Models (LLMs)
  • PyTorch
  • Hugging Face
  • LangChain
  • VectorDBs
  • open source programming languages
  • machine learning
  • relational databases
  • Python
  • Scala
  • R

Nice to have

  • PhD in STEM field
  • AWS
  • managing people

What the JD emphasized

  • track record of delivering models at scale
  • experience in training language models
  • expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF

Other signals

  • LLM Customization
  • building production systems
  • applying state of the art AI
  • delivering models at scale