Role OverviewAs a Materials Science PhD - AI Evaluator - AI Trainer, you will work independently and asynchronously to meet deadlines and improve AI model performance. You will source material from published papers, Kaggle datasets, open-source repositories, or designed scenarios, and write scientific prompts based on sourced input to challenge AI models.
What You Will Do
Your main day-to-day responsibilities will include building grading criteria to define correct answers for scientific tasks, calibrating tasks against frontier models, and ensuring tasks ship only when strong models fail more often than succeed.
Why It Might Be a Fit
To be a fit for this role, you should have a PhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field, and demonstrated depth in semiconductor materials and molecular modeling.
Requirements
- PhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field
- Demonstrated depth in semiconductor materials and molecular modeling
- Working proficiency in Python, R, or another relevant programming language for scientific computing
- Comfortable with Git/GitHub and running code in Docker
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