Description

You will design and implement a real-time visualization and monitoring toolkit for federated and distributed training workflows.

This role is remote.

Responsibilities

• Design and implement a real-time, distributed visualization and monitoring toolkit integrated with APPFL.
• Implement features and algorithms for privacy-preserving, large-scale federated learning.
• Optimize the APPFL framework for efficiency in large-scale federated training.
• Provide ongoing maintenance, bug fixes, and release support for the APPFL codebase.
• Refactor the codebase and improve documentation for community usability and adoption.

Required Skills

• 10+ years of experience with Python.
• Experience with Github and open-source framework maintenance.
• Experience designing extensible architectures for metric collection and visualization.
• Experience with distributed and federated learning workflows.
• Ability to optimize performance and memory footprints in large-scale experiments.
• Familiarity with developing monitoring tools comparable to MLFlow or Weights & Biases.
• Experience with release cycles and codebase refactoring.

Key Skills

Education

Not specified