ML Engineer IV — Python, AWS, GenAI, Production Scale

Capital One National Association; Richmond, Northern (CA, KY); Hybrid; USD 215,000 - 245,000; Full time

Benefits offered by this job

Performance incentives

Capital One Benefits

Job summary

Capital One is seeking a Machine Learning Engineer 4 to design, train, and deploy scalable ML models in a fast-paced, collaborative environment. You’ll work with Python, data pipelines, and cloud platforms to deliver production-ready AI solutions across EPTech.

Strong emphasis on responsible AI and secure code practices in an Agile team. You’ll join the Enterprise Platforms Technology group, contributing to hyper-personalized messaging platforms and scalable ML workloads in production.

Qualifications

• Bachelor's degree or higher in CS or a related quantitative field.
• 4+ years of programming with Python, Java, Golang, or C++.
• 4+ years of ML using PyTorch or TensorFlow with Pandas/NumPy/Scikit-learn.
• 4+ years with large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production in the cloud (AWS/GCP/Azure) and using Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infra decisions: model choice, data, features, training, tuning, validation.
• Write production-grade code, train/validate models, and automate tests and deployment.
• Collaborate in an Agile cross-functional team for big data and ML applications.
• Retrain, monitor, and maintain models in production; build scalable data pipelines.
• Apply CI/CD, test automation, and governance to ensure secure, compliant models.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

CI/CD

AWS

GCP

Azure

Education

Bachelor's Degree

Master's or Doctoral Degree

Tools

Docker

Kubernetes

Spark

Ray

CI/CD

Job description

Capital One is seeking a Machine Learning Engineer 4 to design, train, and deploy scalable ML models in a fast-paced, collaborative environment. You’ll work with Python, data pipelines, and cloud platforms to deliver production-ready AI solutions across EPTech.

Strong emphasis on responsible AI and secure code practices in an Agile team. You’ll join the Enterprise Platforms Technology group, contributing to hyper-personalized messaging platforms and scalable ML workloads in production.