Senior ML Engineer - Production AI & Scale

Capital One; McLean (VA); Hybrid; USD 197.000 - 225.000; Vollzeit

Zusammenfassung

Capital One is seeking a Machine Learning Engineer to design, build, and deploy production ML models at scale. You will work with Product and Data Science teams to choose architectures, train models, and monitor performance in real-time.

The role requires strong programming skills (Python/Java/Golang/C++), experience with PyTorch or TensorFlow, and expertise in distributed systems (Spark/Ray). Cloud and Kubernetes experience are essential for production pipelines.

Qualifikationen

• Bachelor's degree in CS or a related quantitative field is required.
• 4+ years programming experience in Python, Java, Golang, or C++.
• 4+ years ML experience with PyTorch or TensorFlow.
• 4+ years deploying and operating large-scale distributed systems (Spark, Ray).
• 4+ years deploying and operating ML solutions in production in the cloud (AWS, GCP, Azure) and using Kubernetes.

Aufgaben

• Design, build, and deliver ML models and components that solve real-world business problems, in collaboration with Product and Data Science teams.
• Inform ML infrastructure decisions, including model choice, data, feature selection, training, tuning, and validation.
• Write and test application code, develop and validate ML models, and automate tests and deployments.
• Collaborate in a cross-functional Agile team to create software enabling state-of-the-art ML applications.
• Retrain, monitor, and maintain models in production; ensure governance and responsible AI practices.
• Build optimized data pipelines and leverage cloud architectures to deliver scalable ML models.

Kenntnisse

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

Kubernetes

AWS

GCP

Azure

Ausbildung

Bachelor's degree in Computer Science or related quantitative field

Master's or PhD in Computer Science, Electrical Engineering, Mathematics, or related field

Tools

Kubernetes

Jobbeschreibung

Capital One is seeking a Machine Learning Engineer to design, build, and deploy production ML models at scale. You will work with Product and Data Science teams to choose architectures, train models, and monitor performance in real-time.

The role requires strong programming skills (Python/Java/Golang/C++), experience with PyTorch or TensorFlow, and expertise in distributed systems (Spark/Ray). Cloud and Kubernetes experience are essential for production pipelines.