Senior Machine Learning Engineer – Scalable AI Platforms

Capital One National Association; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models and data pipelines in a collaborative, cross‑functional Agile team. You will work on production systems, monitor models, and leverage cloud architectures for large-scale AI solutions.

The role emphasizes hands-on development in Python/Java/Golang/C++, familiarity with PyTorch/TensorFlow, and distributed data processing with Spark or Ray.

Qualifications

• 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 industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn).
• At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data.
• At least 4 years 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 Machine Learning software systems

Responsibilities

• Design, build, and deliver ML models and components in collaboration with Product and Data Science teams.
• Build and scale multi-tenant platforms for large footprint ML training and serving.
• Inform ML infrastructure decisions: model choice, data, features, training, hyperparameters.
• Write and test application code, develop ML models, and automate tests and deployment.
• Collaborate in a cross-functional Agile team to enable state-of-the-art big data and ML apps.
• Retrain, monitor, and maintain models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Construct optimized data pipelines for feeding ML models.
• Apply CI/CD, test automation, and monitoring for reliable deployments.
• Ensure code governance and responsible, explainable AI practices.

Skills

Python/Java/Golang/C++

ML frameworks PyTorch/TensorFlow

Distributed systems Spark/Ray

Cloud deployment Kubernetes

Education

Bachelor's degree or higher in CS/ML or related field

Master's or Doctoral degree (preferred)

Tools

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Job description

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models and data pipelines in a collaborative, cross‑functional Agile team. You will work on production systems, monitor models, and leverage cloud architectures for large-scale AI solutions.

The role emphasizes hands-on development in Python/Java/Golang/C++, familiarity with PyTorch/TensorFlow, and distributed data processing with Spark or Ray.