Research Engineer, Synthetic Data (Fully Remote)

Pragmatike; Stati Uniti; Remoto; USD 110.000 - 170.000; Tempo pieno

Descrizione del lavoro

Pragmatike seeks researchers to analyze model and agent performance on synthetic tasks and to quantify task diversity, realism and learnability. You will build scalable data generation pipelines and develop metrics to assess what the tasks teach models.

The role focuses on improving synthetic data pipelines, understanding data-driven failures, and delivering reliable AI training infrastructure for real-world applications.

Competenze

• Experience with synthetic data research methods.
• Proficiency in Python, Docker and Linux environments.
• Ability to design scalable synthetic data pipelines.

Mansioni

• 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.
• Build the synthetic data pipeline: design the tasks and systems that generate training data at scale.
• See what the data actually teaches: analyse model and agent performance, and improve the tasks when they fail.

Conoscenze

Python

Docker

Linux

Synthetic data research

Descrizione del lavoro

• 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.