Senior Machine Learning Engineer — Production AI & MLOps

Capital One Group; Plano (TX); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer 4 in Plano, TX to design, build, and deploy scalable ML models within an Agile team. You will collaborate with Product and Data Science, optimize data pipelines, and monitor models in production while adhering to security, governance, and compliance standards.

The role requires 4+ years in ML, proficiency with PyTorch/TensorFlow, distributed systems, and cloud deployment with Kubernetes. This is a full-time, on-site position in Plano, TX.

Qualifications

• BS/MS/PhD in CS/ML or related field, with strong quantitative background.
• 4+ years programming in Python/Java/Golang/C++.
• 4+ years ML with PyTorch or TensorFlow.
• 4+ years operating large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production on cloud and using Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Choose models, data, features; train, tune, validate, and test ML solutions.
• Develop scalable data pipelines and ML infrastructure in production.
• Collaborate in an Agile cross-functional team to advance ML applications.
• Monitor, retrain, and govern models; ensure security and compliance.

Skills

Python/Java/Golang/C++

ML frameworks (PyTorch/TensorFlow)

Distributed systems (Spark/Ray)

Cloud deployment (AWS/GCP/Azure)

Education

Bachelor's degree or higher in CS/ML or related field

Master's or Doctoral degree (preferred)

Tools

Kubernetes

Job description

Capital One is seeking a Machine Learning Engineer 4 in Plano, TX to design, build, and deploy scalable ML models within an Agile team. You will collaborate with Product and Data Science, optimize data pipelines, and monitor models in production while adhering to security, governance, and compliance standards.

The role requires 4+ years in ML, proficiency with PyTorch/TensorFlow, distributed systems, and cloud deployment with Kubernetes. This is a full-time, on-site position in Plano, TX.