Lead Machine Learning Engineer

Capital One Financial

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Salary
$197,300–$225,100 / yr
Posted
3 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $220k
This role $211k
$176k most similar roles pay here $267k

This role pays less than 53% of similar roles. Most pay $194,125–$246,150 — the shaded band above. At the midpoint, this role pays about $211k versus about $220k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Machine Learning Engineer

Lead Machine Learning Engineer (Python, GoLang, AWS) joins an Agile team focused on productionizing machine learning applications and systems at scale. This role involves technical design, development, and implementation of machine learning architectures while ensuring high availability and performance for all models. The engineer will build and deliver ML components to solve real-world business problems, construct optimized data pipelines, and manage model retraining, monitoring, and governance regarding Responsible and Explainable AI. Day-to-day tasks include writing and testing application code, automating deployments through CI/CD best practices, and collaborating with cross-functional teams to enhance big data applications. The role requires proficiency in Python, GoLang, Scala, or Java, along with experience in distributed computing and cloud-based architectures. The work centers on solving complex technical problems by integrating machine learning modeling techniques into robust, scalable production environments.

What you'll do

  • Design, build, and deliver machine learning models and components that solve real-world business problems.
  • Develop and review model and application code while ensuring high availability and performance.
  • Construct optimized data pipelines to feed machine learning models.
  • Build and manage cloud-based architectures and technologies to deliver ML models at scale.
  • Retrain, maintain, and monitor machine learning models in production environments.
  • Implement CI/CD best practices, including test automation and monitoring, for model deployment.
  • Ensure all code is managed to reduce vulnerabilities and follows Responsible and Explainable AI principles.

What we're looking for

  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
  • 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.
  • 3+ years of experience building production-ready data pipelines that feed ML models (preferred).

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