Lead ML Ops Engineer — Platform & Infra

Capital One

McLean (VA)

On-site

USD 197,000 - 225,000

Full time

14 days+
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Job summary

Capital One is seeking a Lead Software Engineer focusing on MLOps to bridge software engineering, cloud infrastructure, and data science. You will lead teams delivering scalable ML infrastructure, productionizing data pipelines, and driving a major technology transformation.

You’ll work with AWS, Docker/Kubernetes, PyTorch/TensorFlow, and Spark to deploy models, monitor systems, and ensure resilience in real‑time, high‑stakes applications. Collaboration with product teams is essential.

Qualifications

  • Bachelor's Degree required; experience in Python/Java/Scala is expected.
  • Strong background in ML infrastructure, data pipelines, and model deployment.
  • Experience with cloud platforms (AWS) and scalable ML systems.

Responsibilities

  • Lead software and MLOps projects; mentor developers and drive Agile practices.
  • Own end-to-end MLOps lifecycle: from research models to scalable production deployment.
  • Design and optimize data pipelines, model serving, and monitoring for high-stakes apps.
  • Write performant code in Python; Java/Scala as secondary stacks; emphasize resiliency.
  • Balance hands-on coding with technical leadership and cross-functional rollout coordination.
  • Leverage AWS, Docker/Kubernetes, PyTorch/TensorFlow, Spark to automate deployment.

Skills

Python
Scala/Java
Cloud AWS
ML systems
Agile practices
Mentoring

Education

Bachelor's Degree

Tools

Docker
Kubernetes
PyTorch
TensorFlow
Spark

Job description

Capital One is seeking a Lead Software Engineer focusing on MLOps to bridge software engineering, cloud infrastructure, and data science. You will lead teams delivering scalable ML infrastructure, productionizing data pipelines, and driving a major technology transformation.

You’ll work with AWS, Docker/Kubernetes, PyTorch/TensorFlow, and Spark to deploy models, monitor systems, and ensure resilience in real‑time, high‑stakes applications. Collaboration with product teams is essential.

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