Machine Learning Engineer - Production ML on Python/AWS

Capital One National Association; Plano (TX); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One in Plano, TX is seeking a Machine Learning Engineer 4 to design, build, and operate ML models and data pipelines at scale. You’ll collaborate with Product and Data Science teams to deliver production-grade solutions using Python, AWS, and modern ML frameworks.

You’ll retrain, monitor, and optimize models in production, implement responsible AI practices, and contribute to cloud-based architectures and CI/CD processes in a fast-paced, inclusive environment.

Qualifications

• Bachelor's Degree or higher in Computer Science, Machine Learning or related quantitative field
• At least 4 years of experience programming with Python, Java, Golang, or C++
• At least 4 years of Machine Learning experience using PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn)
• At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 2 years of experience deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems

Responsibilities

• Design, build, and deliver ML models and components solving real-world problems
• Inform ML infrastructure decisions including model, data, and feature selection
• Retrain, monitor, and maintain models in production
• Collaborate in a cross-functional Agile team to create and enhance software for ML apps
• Leverage CI/CD and test automation to ensure successful deployment of ML models and code

Skills

Python

Java

Golang

C++

Education

Bachelor's degree in CS/ML or related

Tools

PyTorch

TensorFlow

Spark

Kubernetes

AWS

Job description

Capital One in Plano, TX is seeking a Machine Learning Engineer 4 to design, build, and operate ML models and data pipelines at scale. You’ll collaborate with Product and Data Science teams to deliver production-grade solutions using Python, AWS, and modern ML frameworks.

You’ll retrain, monitor, and optimize models in production, implement responsible AI practices, and contribute to cloud-based architectures and CI/CD processes in a fast-paced, inclusive environment.