Lead ML Engineer: Scalable AI & Production Systems

Capital One; Boston (MA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One seeks a Lead Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design, implement, and optimize ML models and systems, collaborating with product and data science teams to deliver enterprise-grade solutions.

You will work across ML infrastructure, data pipelines, and deployment practices, using Python/Scala/Java and modern frameworks. Strong cloud experience and a track record in scalable ML are valued.

Qualifications

• Bachelor’s degree in a relevant field.
• At least 6 years designing and building data-intensive solutions using distributed computing.
• At least 4 years programming with Python, Scala, or Java.
• At least 2 years building, scaling, and optimizing ML systems.
• Master’s or Doctoral degree preferred and 3+ years experience with ML pipelines and cloud platforms.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infrastructure decisions including model choice, data, features, and validation.
• Write, test, and deploy production-ready ML code and models.
• Collaborate in a cross-functional Agile team to enable scalable ML apps.
• Retrain, monitor, and maintain models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Construct data pipelines to feed ML models.
• Apply CI/CD, test automation, and monitoring for deployments.
• Ensure governance, risk controls, and responsible AI best practices.
• Use Python, Scala, or Java for implementation.

Skills

Python

Scala

Java

Education

Bachelor’s degree

Master’s or Doctoral degree (preferred)

Tools

scikit-learn

PyTorch

TensorFlow

Spark

Dask

Job description

Capital One seeks a Lead Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design, implement, and optimize ML models and systems, collaborating with product and data science teams to deliver enterprise-grade solutions.

You will work across ML infrastructure, data pipelines, and deployment practices, using Python/Scala/Java and modern frameworks. Strong cloud experience and a track record in scalable ML are valued.