Lead Machine Learning Engineer, Intelligent Foundations and Experiences

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type
On-site
Location
New York, NYMcLean, VA
Employment
Full-time
Posted
57 days ago
Freshness
Confirmed live today

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Salary context

How this pay compares to similar roles

Similar $230k
$168k $289k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $206,175–$254,750.

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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Lead Machine Learning Engineer, Intelligent Foundations and Experiences

The Lead Machine Learning Engineer - Intelligent Foundations and Experiences (IFX) joins an Agile team focused on productionizing machine learning applications and systems at scale. This role involves the technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Key responsibilities include building and delivering ML models to solve real-world business problems, designing cloud-based architectures, and constructing optimized data pipelines. The engineer will retrain, maintain, and monitor production models while ensuring high availability and performance. Required technical skills include proficiency in Python, Scala, or Java, along with experience in distributed computing and ML frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. The work centers on solving complex problems through automated testing, continuous deployment, and Responsible and Explainable AI practices.

What you'll do

  • Design, build, and deliver machine learning models and components to solve real-world business problems.
  • Develop and validate application code while automating tests and deployment processes.
  • Retrain, maintain, and monitor machine learning models in production environments.
  • Construct optimized data pipelines to feed machine learning models.
  • Build and leverage cloud-based architectures to deliver optimized ML models at scale.
  • Implement continuous integration and continuous deployment best practices for model deployment.
  • Ensure all code and models follow best practices for Responsible and Explainable AI.

What we're looking for

  • At least 6 years of experience designing and building data-intensive solutions using distributed computing.
  • At least 4 years of experience programming with Python, Scala, or Java.
  • At least 2 years of experience building, scaling, and optimizing ML systems.
  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
  • 3+ years of experience building production-ready data pipelines that feed ML models (preferred).
  • 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).
  • 2+ years of experience developing performant, resilient, and maintainable code (preferred).

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