Senior ML Engineer — Scale Production AI

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

Job summary

Capital One is hiring a Machine Learning Engineer 4 (IC) in the New York area. You will design, build, and deploy ML models at scale, collaborating with Product and Data Science teams to solve real business problems.

You’ll work with Python/Java, PyTorch or TensorFlow and manage ML pipelines in cloud environments (AWS/GCP/Azure) using Kubernetes, Spark, and modern CI/CD practices. This role requires 4+ years of ML and distributed systems experience.

Qualifications

• Bachelor’s degree or higher in CS, ML or related quantitative field.
• 4+ years of experience programming with Python/Java/Golang/C++ and ML with PyTorch or TensorFlow.
• 4+ years of experience using and operating large-scale distributed systems (Spark, Ray) for AI/ML data.
• 4+ years deploying and operating ML solutions in production 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 with Product and Data Science teams.
• Inform ML infrastructure decisions using modeling techniques, data, and feature selection.
• Develop production-grade code, validate models, and automate tests and deployment.
• Collaborate in cross-functional Agile teams to create scalable ML apps.
• Retrain, monitor, and maintain models in production.
• Construct optimized data pipelines feeding ML models.
• Apply CI/CD, testing, and monitoring for successful deployment.
• Ensure code governance and Responsible AI practices.

Skills

Python

Java

ML Engineering

Spark

Kubernetes

AWS

CI/CD

Model deployment

Education

Bachelor's degree in CS or related field

Tools

PyTorch

TensorFlow

Keras

Spark

Hadoop

Docker

Kubernetes

Airflow

Job description

Capital One is hiring a Machine Learning Engineer 4 (IC) in the New York area. You will design, build, and deploy ML models at scale, collaborating with Product and Data Science teams to solve real business problems.

You’ll work with Python/Java, PyTorch or TensorFlow and manage ML pipelines in cloud environments (AWS/GCP/Azure) using Kubernetes, Spark, and modern CI/CD practices. This role requires 4+ years of ML and distributed systems experience.