Lead ML Engineer: GenAI, Python & AWS at Scale

COMFORT SYSTEMS; San Francisco (CA); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One seeks a Lead Machine Learning Engineer in San Francisco, CA to productionize ML applications at scale, collaborating with Product and Data Science to design robust architectures and scalable pipelines.

You will build and review ML models, perform deployment, testing, and monitoring while ensuring governance and responsible AI practices within a cross-functional Agile team.

Qualifications

• Bachelor’s Degree required; 6+ years building data-intensive solutions on distributed systems.
• 4+ years programming in Python, Scala, or Java.
• 2+ years of experience building, scaling, and optimizing ML systems.
• Master’s or Doctoral degree preferred; multiple years building production ML pipelines.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infrastructure decisions: data, feature selection, training, validation, deployment.
• Write and test application code, automate ML model deployment and tests.
• Collaborate in a cross-functional Agile team to enable big data and ML apps.
• Retrain, monitor, and maintain models in production; ensure governance and risk controls.

Skills

Python

Scala

Java

AWS

SQL

GenAI

Education

Bachelor’s Degree

Master’s Degree

Tools

scikit-learn

PyTorch

Spark

TensorFlow

Job description

Capital One seeks a Lead Machine Learning Engineer in San Francisco, CA to productionize ML applications at scale, collaborating with Product and Data Science to design robust architectures and scalable pipelines.

You will build and review ML models, perform deployment, testing, and monitoring while ensuring governance and responsible AI practices within a cross-functional Agile team.