Senior ML Engineer — Production ML & MLOps

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

Job summary

Capital One is seeking a seasoned Machine Learning Engineer (MLE) to join the IFX team. You’ll design, build, and productionize ML models at scale, collaborating with Product and Data Science to deliver real-world impact for millions of customers.

You’ll work on ML infrastructure, data pipelines, model validation, deployment, and monitoring, using Python, Scala, or Java, and applying responsible AI practices in a fast-paced Agile environment.

Qualifications

• Bachelor’s degree in a relevant field.
• 6+ years designing data-intensive solutions using distributed computing.
• 4+ years programming with Python, Scala, or Java.
• 2+ years building, scaling, and optimizing ML systems.

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems, with Product and Data Science teams.
• Inform ML infrastructure decisions, including model, data, and feature selection, training and validation.
• Write and test application code, develop and validate ML models, and automate tests and deployment.
• Collaborate in an Agile team to enable state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage cloud-based architectures to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Follow CI/CD and monitoring to ensure successful deployments.
• Ensure code and models governance, and Responsible AI practices.
• Use Python, Scala, or Java in development.

Skills

Distributed computing

Python

Scala/Java

ML systems

CI/CD

Model evaluation

Education

Bachelor's degree

Master's or doctoral

Tools

scikit-learn

PyTorch

Dask

Spark

TensorFlow

Job description

Capital One is seeking a seasoned Machine Learning Engineer (MLE) to join the IFX team. You’ll design, build, and productionize ML models at scale, collaborating with Product and Data Science to deliver real-world impact for millions of customers.

You’ll work on ML infrastructure, data pipelines, model validation, deployment, and monitoring, using Python, Scala, or Java, and applying responsible AI practices in a fast-paced Agile environment.