Senior ML Engineer - Scalable Production ML Architect

Capital One; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Job summary

Capital One is seeking an experienced Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design and implement ML components, build data pipelines, and shape the ML architecture across platforms, using Python, Scala, or Java.

You will lead ML initiatives, collaborate with data science and product teams, and ensure high availability, governance, and performance of ML systems.

Qualifications

• Bachelor’s Degree required; 8+ years of data-intensive distributed computing experience.
• 4+ years programming with Python, Scala, or Java.
• 3+ years building, scaling, and optimizing ML systems.
• 3+ years leading teams developing ML solutions.
• 4+ years with industry ML frameworks (scikit-learn, PyTorch, Spark, XGBoost).
• Experience delivering production ML and data pipelines.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infra decisions, including model/data/feature choices and validation.
• Write and test application code, validate ML models, and automate tests/deployment.
• Collaborate in an Agile cross-functional team to enable big data and ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud-based architectures to deliver scalable ML models.
• Build optimized data pipelines feeding ML models.
• Apply CI/CD, test automation, and monitoring for deployment success.
• Ensure code security, model governance, and responsible/Explainable AI practices.
• Use Python, Scala, or Java for development.

Skills

Python

Scala

Java

Distributed computing

ML modeling

CI/CD

Cloud architecture

Education

Bachelor's Degree

Master's or Doctoral Degree

Tools

AWS

Azure

Google Cloud Platform

Job description

Capital One is seeking an experienced Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design and implement ML components, build data pipelines, and shape the ML architecture across platforms, using Python, Scala, or Java.

You will lead ML initiatives, collaborate with data science and product teams, and ensure high availability, governance, and performance of ML systems.