Machine Learning Engineer

Job Summary (List Format)

• Position:
  Machine Learning Engineer (ML Engineer)

Key Responsibilities

• Operate and maintain ML pipelines built on Quickflow
• Optimize and automate ML workflows
• Scale ML infrastructure to support more customers
• Release new ML models on a weekly basis
• Collaborate closely with Data Engineers on data pipelines and APIs
• Own end-to-end ML infrastructure for decisioning platforms (mobile/web)
• Transition ML models from Reno fast models to transformer models

Must-Have Skills

• Machine Learning Engineering (ML engineering)
• Recent hands-on Capital One project experience
• Strong Python and Scala programming skills
• Experience with Kubernetes for orchestration
• Deep knowledge of ML frameworks:
  Tensor Flow, PyTorch, Scikit-learn
• Real-time data processing expertise

Project Scope

• Work on ML decisioning platforms for campaign arbitration and UI integration
• Inherit and enhance existing ML data/model training pipelines
• Expand ML engineering capabilities within the team
• Focus on feature development and infrastructure scaling

Team Structure

• ML Engineering team collaborating with Data Engineers and Software Engineers
• Spread across NYC and McLean, VA locations
• Role complements an existing Data Engineer (focus on ML engineering tasks)