Senior Manager, Machine Learning Engineer 5, Intelligent Foundations and Experiences

Capital One Financial

Confirmed live yesterday High trust

Quick summary

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

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $229k
This role $246k
$175k $275k
below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $202,800–$254,750 — the blue band above. At the midpoint, this role pays about $246k versus about $229k 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 2203 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1138 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Machine Learning Engineer 5, Intelligent Foundations and Experiences

The Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) joins a team focused on driving major AI transformations and scaling production models. This role involves designing, building, and delivering machine learning models and components to solve real-world business problems while building massive multi-tenant platforms for large-footprint model training and serving. Key responsibilities include constructing optimized data pipelines, automating tests and deployments, and monitoring models in production. The position requires proficiency in Python, Scala, Java, Golang, or C++, along with experience in PyTorch, Tensorflow, Pandas, NumPy, and Scikit-learn. Candidates must operate large-scale distributed systems using Spark and Ray, manage containerized software via Kubernetes, and utilize cloud platforms like AWS, GCP, or Azure to deliver optimized, responsible, and explainable AI solutions.

What you'll do

  • Design, build, and deliver ML models and components to solve real-world business problems.
  • Build and scale massive multi-tenant platforms for large-footprint ML model training and serving.
  • Write and test application code while automating tests and deployment processes.
  • Retrain, maintain, and monitor ML models in production environments.
  • Construct optimized data pipelines to feed ML models for training and evaluation.
  • Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
  • Implement continuous integration and continuous deployment best practices for ML models and application code.
  • Ensure models follow best practices in Responsible and Explainable AI and meet risk governance standards.

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 or Tensorflow and libraries like Pandas, NumPy, and Scikit-learn.
  • At least 6 years of experience using and operating large scale distributed systems like Spark or Ray to prepare AI data.
  • At least 4 years of experience deploying and operating 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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