Bright C.

Key Skills

Software

Don't disclose

Micro1

Mercor

Label Studio

Redbrick AI

Top Subject Matter

Large Language Model (LLM) response evaluation and RLHF training

AI assessment benchmarking and quality validation

Legal Services & Contract Review

Top Data Types

Text

Document

Top Task Types

Prompt + Response Writing (SFT)

Freelancer Overview

AI Data Annotator & Evaluator (Freelance / Contract) — Remote (2024–Present). Brings 10+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose. Education includes Bachelor of Science, PPSMB (2017). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

AI Assessment Benchmarking (Training/Screening Assessments) — 2024–Present

Don't discloseTextPrompt + Response Writing (SFT)

AI Assessment Benchmarking and proficiency screening for leading global AI platforms focused on linguistic nuance and factual verification. The work emphasizes prompt constraints and evaluating the correctness of generated outputs under test conditions. This role aligns with AI training data preparation and quality-focused assessment tasks. • Complete advanced screening assessments for AI platforms • Demonstrate elite performance in linguistic nuance and instruction following • Apply factual verification to generated content under prompt constraints • Perform evaluation-style work to support AI assessment processes

2024 - Present

AI Data Annotator & Evaluator (Freelance / Contract) — Remote (2024–Present)

Don't discloseText

AI Data Annotator & Evaluator performing RLHF-style evaluation of Large Language Model outputs using strict quality metrics. The work includes ranking responses by helpfulness, truthfulness, safety, clarity, and formatting, and writing justification to explain why one response is better. Additional quality tasks involve deep fact-checking and hallucination detection through cross-referencing primary sources. • Design, execute, and refine prompts to train/steer LLM behavior across domains • Evaluate and rank model responses using rubric-based criteria (helpfulness, truthfulness, safety, clarity, formatting) • Perform deep-dive fact-checking to identify, document, and eliminate hallucinations • Write justification essays that support the RLHF training cycle

2024 - Present

Education

Work History