Large-scale data processing platform
A containerized annotation platform handling a million-word dataset, orchestrated across a distributed team.
The problem
A Japanese corporate client needed over 1 million words of text annotated for machine learning, but manual annotation workflows couldn't scale to that volume or stay consistent across a distributed international team.
What I built
Architected and deployed a containerized data annotation platform, orchestrating processing workflows in Kubernetes so work could scale horizontally against the dataset. Docker-based packaging kept the annotation toolchain identical for every team member, regardless of where they worked from.
Outcome
1M+
Japanese words in the annotated dataset
Kubernetes
Horizontal scaling for distributed processing
Global team
Coordinated across international collaborators
Architecture
The shape of the system after the work. Inspect any component to see the part it plays.
Select a component to see its role in the system.