Senior ML Engineer — Production AI & Scalable Systems

Capital One; Chicago (IL); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer 4 (Manager, IC) to design, build, and deploy scalable ML models in a fast-paced, collaborative environment. You’ll work with Product and Data Science teams to solve real-world business problems and inform ML infrastructure decisions.

You will train, deploy, and monitor models in production, build data pipelines, and ensure governance and responsible AI practices while leveraging cloud platforms (AWS, GCP, Azure) and Kubernetes for scale.

Qualifications

• Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 4 years of experience programming with Python, Java, Golang, or C++
• At least 4 years of Machine Learning experience using PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn)
• At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
• At least 2 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 ML software systems

Responsibilities

• Design, build, and/or deliver ML models and components that solve real-world business problems with Product and Data Science teams
• Inform ML infrastructure decisions including model choice, data, feature selection, training, and validation
• Write and test application code, develop and validate ML models, and automate tests and deployment
• Collaborate in an Agile cross-functional team to create software enabling big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage cloud architectures to deploy optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Use CI/CD principles, test automation, and monitoring for deployment
• Ensure code governance and responsible AI practices
• Use Python, Scala, or Java for development

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

Master's or Doctoral Degree (preferred)

Tools

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One is seeking a Machine Learning Engineer 4 (Manager, IC) to design, build, and deploy scalable ML models in a fast-paced, collaborative environment. You’ll work with Product and Data Science teams to solve real-world business problems and inform ML infrastructure decisions.

You will train, deploy, and monitor models in production, build data pipelines, and ensure governance and responsible AI practices while leveraging cloud platforms (AWS, GCP, Azure) and Kubernetes for scale.