Machine Learning Engineer 4 at Capital One

Compensation

$197,300 – $225,100/yr

Location: Cambridge, Massachusetts · Richmond, Virginia · +1
Type: Full-time
Level: senior
Posted: Sep 22, 2026

Description

Capital One is hiring a Machine Learning Engineer 4 for its Risk Tech and GRC teams to design, build, deploy, monitor, and scale production machine learning models and data pipelines. The role involves Python, Scala, or Java development; distributed systems; cloud infrastructure; Kubernetes; CI/CD; and responsible AI practices. Candidates need a bachelor's degree or higher in a relevant quantitative field, at least four years of programming and machine learning experience, and at least two years of production deployment experience. The role is available in Cambridge, McLean, and Richmond, with annual salaries ranging from $179,400 to $225,100 depending on location, and does not offer employer-sponsored work authorization.

Required Skills

Python
PyTorch
TensorFlow
Spark
Kubernetes
AWS
GCP
Azure
CI/CD
Responsible AI

Additional Information

Minimum Education: Bachelor's degree or higher in Computer Science, Machine Learning, or a related quantitative field
Required Previous Experiences: At least 4 years of programming experience with Python, Java, Golang, or C++
At least 4 years of machine learning experience using PyTorch or TensorFlow and related libraries
At least 4 years of experience operating large-scale distributed systems such as Spark or Ray
At least 2 years of experience deploying and operating machine learning solutions in production on cloud platforms and using Kubernetes
Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
3+ years of experience optimizing machine learning algorithms, configurations, and infrastructure
3+ years of experience following software development best practices
3+ years of experience building resilient software solutions with advanced deployment and monitoring practices
3+ years of experience with machine learning techniques, models, architectures, training concepts, and model evaluation
3+ years of experience designing and scaling production-ready data pipelines
1+ years of experience as a technical lead developing machine learning solutions
Experience authoring or co-authoring a paper on a machine learning technique, model, or proof of concept