Senior ML Engineer: Build Scalable Production Models

Capital One; New York (NY); On-site; USD 177,000 - 201,000; Full time

Job summary

Capital One is seeking a Senior Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design, build, and deploy ML models and data pipelines, collaborating with Product and Data Science teams to solve real-world problems.

The role emphasizes ML infrastructure decisions, CI/CD practices, model retraining/monitoring, and cloud-based deployment across multiple locations in the US.

Qualifications

• Bachelor’s Degree required.
• 4+ years programming with Python, Scala, or Java.
• 3+ years designing data-intensive solutions using distributed computing.
• 2+ years experience with ML frameworks (scikit-learn, PyTorch, Spark, or TensorFlow).
• 1+ year productionizing, monitoring, and maintaining models.

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems, while collaborating with Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including model selection, data and feature choices, training, tuning, validation.
• Write and test application code, develop and validate ML models, and automate tests and deployment.
• Collaborate with a cross-functional Agile team to create and enhance software for 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 best practices including test automation and monitoring.
• Ensure code governance and Responsible AI practices.
• Use Python, Scala, or Java.

Skills

Python

Scala

Java

Distributed computing

Education

Bachelor’s degree

Master’s degree

Tools

scikit-learn

PyTorch

Dask

Spark

TensorFlow

Job description

Capital One is seeking a Senior Machine Learning Engineer to join an Agile team focused on productionizing ML applications at scale. You will design, build, and deploy ML models and data pipelines, collaborating with Product and Data Science teams to solve real-world problems.

The role emphasizes ML infrastructure decisions, CI/CD practices, model retraining/monitoring, and cloud-based deployment across multiple locations in the US.