Machine Learning Engineer (AI Foundations)

Capital One Financial

Quick summary

Work type
On-site
Location
McLean, VA · New York, NY
Salary
$135,600–$154,800 / yr
Posted
1 day ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $213k
This role $145k
$121k most similar roles pay here $273k

This role pays less than 93% of similar roles. Most pay $178,636–$247,875 — the shaded band above. At the midpoint, this role pays about $145k versus about $213k 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 798 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 791 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Machine Learning Engineer (AI Foundations)

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Capital One’s AI Foundations team is seeking a Machine Learning Engineer to contribute to the development of advanced large language models and autonomous systems that enhance banking experiences for millions of customers. This role involves designing data-intensive solutions using distributed computing frameworks, programming with Python or similar languages, and implementing responsible AI practices. The ideal candidate will have at least two years of experience in building production-ready data pipelines and working with industry-recognized ML frameworks like PyTorch or TensorFlow. Additionally, familiarity with large codebases, distributed file systems, and multi-node database paradigms is essential, as well as a track record of contributing to open-source ML software.

Skills

Python Scala Java scikit-learn PyTorch Dask Spark TensorFlow distributed computing distributed file systems multi-node database paradigms data pipelines CI/CD

What you'll do

  • Design and build data-intensive solutions using distributed computing.
  • Program with Python, Scala, or Java to develop machine learning models.
  • Build production-ready data pipelines feeding ML models in a team environment.
  • Work with large code bases and contribute to open-source ML software.
  • Ensure operational efficiency and scalability of AI systems developed.

What we're looking for

  • At least 2 years of experience designing and building data-intensive solutions using distributed computing.
  • Proficient in Python, Scala, or Java with at least 2 years of programming experience.
  • Minimum 1 year of practical machine learning experience with industry-standard frameworks.
  • Experience working on large codebases and contributing to open-source ML software.
  • Strong background in building production-ready data pipelines for ML models.
  • Familiarity with distributed file systems and multi-node database paradigms.

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