Senior Machine Learning Engineer — Scale Production AI

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking Machine Learning Engineers to join our AI and technology teams in McLean, VA. You’ll be on the forefront of building production ML models, collaborating across Product, Data Science, and Ops to solve real business problems and scale capabilities.

We expect strong coding skills (Python/Java/Golang/C++) and hands-on experience with PyTorch or TensorFlow, Spark or Ray, and cloud platforms (AWS, GCP, Azure).

Qualifications

• Bachelor's degree or higher in CS, ML, or related quantitative field.
• At least 4 years programming with Python, Java, Golang, or C++.
• At least 4 years ML experience with PyTorch or TensorFlow and pandas/numpy/scikit-learn.
• At least 4 years experience with large-scale distributed systems (Spark, Ray).
• At least 2 years deploying ML solutions in production and using Kubernetes in cloud environments (AWS, GCP, Azure).

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform infrastructure decisions, including model choice, data, features, training, and validation.
• Write production code, validate ML models, and automate tests and deployment.
• Collaborate in an Agile cross-functional team to enable big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures and pipelines to deliver ML models at scale.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

AWS

GCP

Azure

Kubernetes

Education

Bachelor's degree in Computer Science, Machine Learning or related field

Master's or Doctoral Degree in a related field

Job description

Capital One is seeking Machine Learning Engineers to join our AI and technology teams in McLean, VA. You’ll be on the forefront of building production ML models, collaborating across Product, Data Science, and Ops to solve real business problems and scale capabilities.

We expect strong coding skills (Python/Java/Golang/C++) and hands-on experience with PyTorch or TensorFlow, Spark or Ray, and cloud platforms (AWS, GCP, Azure).