Generalist - English & Punjabi (Train AI Models Part Time!)

hackajob is collaborating with Mercor to connect them with exceptional professionals for this role.

**PLEASE NOTE: You must take the Bilingual Competency interview in Punjabi to be considered for this role.**

**Location**: Global
**Type**: Contract Work
**Fluent Language Skills Required:** Punjabi (native fluency) and English (strong proficiency)

**Why this role matters:** Your job is to assess Punjabi AI-generated responses and identify specific strengths and areas of improvement for these responses – your work will be used to create the "perfect AI-generated response" at a later stage of this project. Note the analysis you create will be in English.

**What You'll Do**

- Conduct fact-checking using trusted public sources and external tools

- Generate high-quality human evaluation data by identifying response strengths, areas for improvement, and factual inaccuracies

- Assess reasoning quality, clarity, tone, and completeness of responses

- Ensure model responses align with expected conversational behavior and system guidelines

**Who You Are**

- You hold a **Bachelor's degree**

- You are a **native speaker** in **Punjabi**

- You have **significant experience using large language models** (LLMs) and understand how and why people use them

- You have **excellent writing skills in English** and can clearly articulate nuanced feedback

- You have **strong attention to detail** and consistently notice subtle issues others may overlook

- You have a background or experience in domains requiring **structured analytical thinking** (e.g., research, policy, analytics, linguistics, engineering)

**Nice-to-Have Specialties**

- Prior experience with **RLHF, model evaluation, or data annotation work**

- Experience writing or editing **high-quality written content**

- Experience comparing multiple outputs and making **fine-grained qualitative judgments**

**What Success Looks Like**

- You identify factual inaccuracies, reasoning errors, and communication gaps in model responses

- You produce clear, consistent, and reproducible evaluation artifacts

- Your feedback leads to measurable improvements in response quality and user experience