Senior ML Engineer (Production-Scale AI)

Capital One; San Jose (CA); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models in production. You will collaborate with product, data science, and engineering teams to deliver state-of-the-art ML applications using Python, Java, or C++. The role emphasizes scalable data pipelines and cloud-based architectures.

You will mentor, retrain, monitor, and optimize models in production, ensuring responsible AI practices and governance across platforms such as AWS, GCP, or Azure.

Qualifications

• Bachelor’s degree in CS or a related quantitative field.
• 4+ years programming in Python, Java, Go or C++.
• 4+ years ML experience with PyTorch or TensorFlow.
• 4+ years with large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production on AWS, GCP or 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 and test application code; automate tests and deployment for ML models.
• Collaborate in a cross-functional Agile team to enable big data and ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures to scale ML models and data pipelines.

Skills

Python

Java

Golang

C++

Machine Learning

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

AWS

GCP

Azure

Education

Bachelor's Degree in Computer Science or related quantitative field

Master's or PhD preferred

Tools

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models in production. You will collaborate with product, data science, and engineering teams to deliver state-of-the-art ML applications using Python, Java, or C++. The role emphasizes scalable data pipelines and cloud-based architectures.

You will mentor, retrain, monitor, and optimize models in production, ensuring responsible AI practices and governance across platforms such as AWS, GCP, or Azure.