Lead ML Engineer – Build & Scale Production AI

Capital One; New York, Northern (NY, KY); Hybride; USD 215 000 - 246 000; Plein temps

Résumé du poste

Capital One is seeking a Machine Learning Engineer 4 (Manager, IC) in New York, NY to design, build, and deploy production ML models at scale. You will collaborate with Product and Data Science teams, shape ML infra decisions, train and validate models, and automate tests and deployments in a fast-paced Agile environment.

This role requires 4+ years in ML and distributed systems, strong experience with PyTorch/TensorFlow, and cloud experience (AWS/GCP/Azure) with Kubernetes.

Qualifications

• Bachelor's degree in CS or related field.
• 4+ years programming with Python/Java/Golang/C++.
• 4+ years ML experience with PyTorch or TensorFlow.
• 4+ years experience with distributed systems (Spark, Ray).
• 2+ years deploying ML in production on cloud (AWS, GCP, Azure) and using Kubernetes.

Responsabilités

• Design, build, and deliver ML models and components with Product/Data Science teams.
• Inform ML infra decisions—model selection, data, features, training, and validation.
• Write and test application code, develop/validate ML models, and automate tests/deployments.
• Retrain, monitor, and maintain models in production; ensure governance and responsible AI practices.
• Collaborate in an Agile cross-functional team to deliver state-of-the-art ML apps.
• Construct data pipelines to feed ML models and enable scalable inference.
• Follow CI/CD, test automation, and monitoring to ensure robust deployment.

Connaissances

Python

Java

Golang

C++

ML engineering

Formation

Bachelor's degree in CS/ML or related field

Outils

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

AWS

GCP

Azure

Description du poste

Capital One is seeking a Machine Learning Engineer 4 (Manager, IC) in New York, NY to design, build, and deploy production ML models at scale. You will collaborate with Product and Data Science teams, shape ML infra decisions, train and validate models, and automate tests and deployments in a fast-paced Agile environment.

This role requires 4+ years in ML and distributed systems, strong experience with PyTorch/TensorFlow, and cloud experience (AWS/GCP/Azure) with Kubernetes.