Machine Learning Engineer V

Capital One Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
McLean, VA
Salary
$229,900–$262,400 / yr
Employment
Full-time
Posted
6 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k
This role $246k
$165k most similar roles pay here $273k

This role pays more than 82% of similar roles. Most pay $187,850–$246,150 — the shaded band above. At the midpoint, this role pays about $246k versus about $217k 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 936 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 933 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Machine Learning Engineer V

Machine Learning Engineer 5 joins a collaborative team to drive major AI transformations and scale production models. This role involves designing, building, and delivering machine learning components that solve real-world business problems while collaborating with Product and Data Science teams. Responsibilities include developing multi-tenant platforms for large-scale model training and serving, constructing optimized data pipelines, and managing the full lifecycle of model retraining, monitoring, and governance. The candidate will work within an Agile framework to build software for big data applications using Python, Scala, or Java. Technical requirements include experience with PyTorch, TensorFlow, Pandas, NumPy, Scikit-learn, Spark, Ray, and Kubernetes across cloud environments like AWS, GCP, or Azure. The role focuses on solving complex business problems by implementing advanced algorithms, ensuring responsible AI practices, and automating deployment through CI/CD pipelines to manage large-scale distributed systems.

What does a Machine Learning Engineer earn in Virginia?

Median $211200 from 41 postings across 3 companies.

See salary data

What you'll do

  • Design, build, and deliver machine learning models and components to solve real-world business problems.
  • Build and scale multi-tenant platforms for large-scale ML model training and serving.
  • Inform infrastructure decisions based on modeling techniques like feature selection, hyperparameter tuning, and validation.
  • Write and test application code while automating tests and deployment processes.
  • Construct optimized data pipelines to feed machine learning models.
  • Retrain, maintain, and monitor models in production environments.
  • Develop cloud-based architectures and technologies to deliver optimized ML models at scale.
  • Ensure all models follow best practices for Responsible and Explainable AI.

What we're looking for

  • Bachelor's degree or higher in Computer Science, Machine Learning, or a related quantitative field.
  • At least 6 years of experience programming with Python, Java, Golang, or C++.
  • At least 6 years of Machine Learning experience using PyTorch, TensorFlow, and libraries like Pandas, NumPy, and Scikit-learn.
  • At least 6 years of experience operating large scale distributed systems such as Spark or Ray to prepare AI/ML data.
  • At least 4 years of experience deploying ML solutions in production using cloud platforms (AWS, GCP, Azure) and Kubernetes.
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field (preferred).
  • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
  • 5+ years of experience following software development best practices including source control, testing, code reviews, and CI/CD (preferred).

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