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: TensorFlow, 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)