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)

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