Senior ML Engineer: Scale Production AI

Capital One; Richmond (VA); Presencial; USD 147.000 - 168.000; Jornada completa

Descripción de la vacante

Capital One is seeking a Machine Learning Engineer to design, build, and deploy ML models at scale, collaborating with Product and Data Science teams in a fast-paced, agile environment.

You will work with Python, Java, Golang, Spark, PyTorch, and TensorFlow, deploying solutions in production on AWS/GCP/Azure and using Kubernetes for orchestration. The role emphasizes monitoring, governance, and Responsible AI practices.

Formación

• Bachelor’s degree in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 3 years of experience programming with Python, Java, Golang, or C++
• At least 2 years of Machine Learning experience using PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn)
• At least 3 years of experience with large scale distributed systems (Spark, Ray)
• At least 1 year deploying ML solutions in production on cloud (AWS, GCP, Azure) and using Kubernetes

Responsabilidades

• Design, build, and deliver ML models and components
• Inform ML infrastructure decisions including model, data, and feature selection
• Write and test application code, develop ML models, and automate tests and deployment
• Collaborate in a cross-functional Agile team to enable big data and ML apps
• Retrain, maintain, and monitor models in production
• Build cloud-based architectures to deliver ML models at scale
• Construct optimized data pipelines for ML feeding
• Implement CI/CD, test automation, and monitoring for ML deployments
• Ensure code governance and responsible/Explainable AI practices

Conocimientos

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

Kubernetes

AWS

GCP

Azure

Educación

Bachelor's degree in CS/ML/related field

Master's degree

PhD

Herramientas

Spark

Ray

Kubernetes

AWS

GCP

Azure

Descripción del empleo

Capital One is seeking a Machine Learning Engineer to design, build, and deploy ML models at scale, collaborating with Product and Data Science teams in a fast-paced, agile environment.

You will work with Python, Java, Golang, Spark, PyTorch, and TensorFlow, deploying solutions in production on AWS/GCP/Azure and using Kubernetes for orchestration. The role emphasizes monitoring, governance, and Responsible AI practices.