AI Trainer – LLM Annotation & Evaluation

About the role

As an AI Trainer specializing in large language model (LLM) annotation and evaluation, you will work on assessing model outputs related to STEM reasoning, coding logic, and multiple‑choice questions. Your work will directly contribute to improving the technical reasoning and coding capabilities of AI agents.

Key responsibilities

• Annotate and evaluate model performance on coding, logical reasoning, and STEM‑related tasks.
• Review Python code snippets, trace execution, judge correctness, and assess multiple‑choice questions accurately.
• Build and maintain high‑quality evaluation datasets for STEM, coding, and reasoning scenarios.
• Follow English project guidelines to ensure consistency and data quality.
• Complete assigned annotation and evaluation tasks on a daily, weekly, and monthly basis.

Required profile

• Diploma or higher in a STEM field such as Computer Science, Software Engineering, Mathematics, Data Science, or related disciplines.
• English literacy at CEFR B1 level or above.
• Ability to perform precise and consistent annotation on coding, logic, and STEM tasks.
• Preferred experience in Python programming, programming education, question‑bank verification, or AI training data annotation.

Required skills

• Basic proficiency in Python syntax, including reading and understanding pseudocode and code snippets.