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What You'll Do:
- Analyse model and agent performance on synthetic tasks to understand what the tasks are teaching and where they fail.
- Develop metrics to quantify and understand synthetic task diversity, realism, learnability and related qualities.
What We're Looking For:
- Proficiency in Python, Docker and Linux environments.
- Experience with synthetic data research methods — please be ready to describe this in your application.
Why This Role Matters For You:
- Build the synthetic data pipeline: You will design the tasks and systems that generate training data at scale, not only run experiments on someone else's pipeline.
- See what the data actually teaches: Analyse model and agent performance, and improve the tasks when they fail.
Pragmatike
They build reliable, fair and open infrastructure for AI training data. The company is backed by Y Combinator, used by startups and Fortune 500, and scaling quickly.