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M
Mayank P.

Mayank P.

India flagGreater Noida, India

Key Skills

Software

Google Cloud Vertex AIGoogle Cloud Vertex AI
Kili TechnologyKili Technology
Label StudioLabel Studio
Scale AIScale AI
SuperAnnotateSuperAnnotate

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
TextText
Computer Code ProgrammingComputer Code Programming

Top Task Types

ClassificationClassification
Text GenerationText Generation
Text SummarizationText Summarization
Question AnsweringQuestion Answering
TranscriptionTranscription
Evaluation/RatingEvaluation/Rating
Computer Programming/CodingComputer Programming/Coding

Freelancer Overview

I have experience working with AI tools, content evaluation, research, and data organization, along with a strong technical background in Computer Science Engineering. Through various academic and professional projects, I have developed skills in analyzing information, identifying patterns, maintaining data accuracy, and following detailed guidelines. I regularly work with AI platforms such as Google Gemini and ChatGPT for content generation, evaluation, testing, and prompt refinement, which has given me a solid understanding of how training data quality impacts AI performance. In addition, I have experience managing digital content, documentation, and large volumes of information through leadership roles, technical projects, and community initiatives. My strengths include attention to detail, strong written communication, internet research, quality checking, and the ability to learn new annotation or labeling frameworks quickly. As a Google Gemini Student Ambassador and Computer Science student, I am comfortable working with technology, adapting to evolving requirements, and delivering accurate, consistent results in AI training and data annotation tasks.

Labeling Experience

AI Response Evaluation and Content Annotation

TextTextTranscriptionTranscription

Evaluated and annotated AI-generated text responses for quality, accuracy, relevance, grammar, and instruction-following. Performed comparative assessments between multiple AI outputs, identified factual inconsistencies, categorized response quality, and provided structured feedback to improve model performance. Worked with diverse content domains including education, technology, business, and general knowledge. Maintained high attention to detail while following annotation guidelines and quality standards. Regularly reviewed outputs for clarity, coherence, safety, and user intent alignment. The work involved data classification, content review, error identification, and quality assurance processes commonly used in AI training and evaluation workflows.

2025 - 2026