ML Engineer III — Build Production AI at Scale

Capital One; Richmond (VA); On-site; USD 147,000 - 168,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models in a fast-paced environment. You will partner with Product, Data Science, and Ops teams to solve real customer problems using Python, Java, and modern ML frameworks.

This role emphasizes production workflows, monitoring, and responsible AI practices. You will work across cloud platforms (AWS/GCP/Azure) and Kubernetes, build data pipelines, and contribute to CI/CD automation.

Qualifications

• Bachelor's Degree or higher in Computer Science, ML or related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 3 years of experience programming with Python, Java, Golang, or C++
• At least 2 years of Machine Learning experience using PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn)
• At least 3 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 1 year of experience deploying and operating Machine Learning 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 that solve real-world business problems, while working with Product and Data Science teams
• Inform ML infrastructure decisions including model, data, feature selection, model training, hyperparameter tuning, validation
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Collaborate in a cross-functional Agile team to create and enhance software enabling scalable ML applications
• Retrain, maintain, and monitor models in production
• Leverage cloud-based architectures and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Use CI/CD and monitoring to ensure successful deployment of ML models and code
• Ensure code is well-governed from risk perspective and following Responsible AI practices

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

AWS

GCP

Azure

Kubernetes

Education

Bachelor's degree in Computer Science or related field

Master's or Doctoral degree preferred

Tools

Spark

Kubernetes

AWS

GCP

Azure

Job description

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models in a fast-paced environment. You will partner with Product, Data Science, and Ops teams to solve real customer problems using Python, Java, and modern ML frameworks.

This role emphasizes production workflows, monitoring, and responsible AI practices. You will work across cloud platforms (AWS/GCP/Azure) and Kubernetes, build data pipelines, and contribute to CI/CD automation.