Senior ML Engineer: Scale Production Models & Pipelines

Capital One National Association; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One National Association is seeking a Machine Learning Engineer 4 in New York, NY to drive AI transformations and scale production models across the business. You'll work with Python/Java/Golang/C++ and leading ML frameworks, collaborating with product and data science teams to deliver real-world solutions.

The role emphasizes building scalable data pipelines, cloud-based architectures, and responsible AI practices, with a focus on production readiness and CI/CD processes.

Qualifications

• Bachelor’s Degree or higher in Computer Science, Machine Learning or a related quantitative field.
• Proficient in Python, Java, Golang, or C++ (4+ years).
• 4+ years ML experience with PyTorch or TensorFlow and Pandas/NumPy/Scikit-learn.
• 4+ years operating large scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production and cloud (AWS, GCP, Azure) with Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Incorporate ML modeling techniques into infra decisions, including data/feature selection, training, validation.
• Write and test application code, develop and validate ML models, automate tests and deployment.
• Collaborate in an Agile team to create software for big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud architectures to deliver optimized ML models at scale.
• Create data pipelines to feed ML models and ensure CI/CD and monitoring.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

AWS

GCP

Azure

Kubernetes

Education

Bachelor’s Degree in Computer Science or related field

Tools

Kubernetes

Spark

Job description

Capital One National Association is seeking a Machine Learning Engineer 4 in New York, NY to drive AI transformations and scale production models across the business. You'll work with Python/Java/Golang/C++ and leading ML frameworks, collaborating with product and data science teams to deliver real-world solutions.

The role emphasizes building scalable data pipelines, cloud-based architectures, and responsible AI practices, with a focus on production readiness and CI/CD processes.