Lucky K.

Key Skills

Software

Other

Top Subject Matter

AI prompt evaluation and quality review

Prompt writing

Testing Domain Expertise

Top Data Types

Text

Computer Code Programming

Top Task Types

Prompt + Response Writing (SFT)

Classification

Fine-tuning

Freelancer Overview

AI Response Evaluation & Quality Review (Learning/Training Focus). Core strengths include Other. Education includes Bachelor of Computer Applications, A.S. College (2026). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

AI Model Training & Fine-tuning Support (Aspiring/Learning)

OtherFine-tuning

Gained preparation for AI model training and fine-tuning support through coursework and self-learning. Studied how labeled/structured data can be used to improve model behavior. Positioned skills toward assisting with training workflows and related evaluation tasks. • Learned concepts related to fine-tuning and model improvement • Focused on accuracy and consistency for training support • Prepared to contribute to AI training pipeline activities • Connected annotation and evaluation understanding to training goals.

2023 - Present

Data Annotation (Learning)

OtherTextClassification

Trained on data annotation concepts with an emphasis on labeling and data preparation for AI systems. Focused on understanding label definitions and applying them consistently to improve dataset quality. Used learning-oriented practice to support data labeling readiness. • Studied annotation principles and label consistency • Applied structured labeling workflows for training purposes • Prepared annotated data aligned with AI use cases • Practiced quality-minded annotation habits for accuracy.

2023 - Present

Prompt Writing & Testing (Learning/Training Focus)

OtherTextPrompt + Response Writing (SFT)

Developed prompt writing and testing skills aligned with AI training and tutoring style workflows. Worked on structuring prompts and validating resulting responses for clarity and task relevance. Emphasized producing consistent, high-quality prompt outputs for downstream AI evaluation. • Wrote and tested prompts for targeted behaviors • Reviewed response quality for relevance and accuracy • Iterated prompts based on observed model behavior • Supported learning objectives in AI training and evaluation.

2023 - Present

AI Response Evaluation & Quality Review (Learning/Training Focus)

Other

Built a foundational practice in AI response evaluation and quality review as part of AI prompting and annotation learning goals. Focused on assessing outputs for correctness, consistency, and adherence to intended prompts. Applied attention to detail to support iterative improvement of AI-assisted responses. • Evaluated prompt–response behavior against expected outcomes • Performed quality checks to identify issues in outputs • Practiced iterative refinement using feedback loops • Learned evaluation criteria aligned with AI/ML quality goals.

2023 - Present

Education

Work History