Suvashis P.

Key Skills

Software

Don't disclose

Top Subject Matter

NLP text annotation (sentiment, intent, classification)

LLM prompt testing and AI response evaluation

LLM prompt writing and iterative refinement

Top Data Types

Text

Top Task Types

Classification

Prompt + Response Writing (SFT)

Freelancer Overview

AI Data Annotation Practice (text classification, sentiment analysis, intent labeling). Core strengths include Don't disclose and ChatGPT. Education includes Higher Secondary Certificate, Keshabpur Govt Pilot Higher Secondary School (2023) and Bachelor's Degree, National University (2027). AI-training focus includes data types such as Text and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

AI Prompt Engineering Practice (prompt writing + response quality improvement)

Don't discloseTextPrompt + Response Writing (SFT)

The experience included prompt engineering practice where prompts for AI language models were designed, tested, and improved. The work incorporated structured evaluation of generated responses to ensure the prompts produced high-quality results. The goal was to enhance AI outputs through careful prompt construction and iterative refinement. • Authored and refined prompts for LLMs • Evaluated outputs for quality and safety alignment • Improved prompt wording to increase usefulness • Documented prompt experiments and outcomes

2023 - 2024

AI Prompt Engineering Practice (prompt testing + response evaluation)

Text

The experience focused on evaluating AI-generated responses from language models for accuracy, relevance, and safety. Prompts were iteratively designed and tested to improve response quality and reduce undesired outputs. The process emphasized prompt testing loops and systematic response evaluation against quality criteria. • Assessed response correctness, relevance, and safety • Tested and revised prompts to improve outcomes • Used evaluation criteria to guide prompt refinements • Iterated based on observed response quality gaps

2023 - 2024

AI Data Annotation Practice (text classification, sentiment analysis, intent labeling)

Don't discloseTextClassification

The experience involved practicing text classification by applying provided annotation guidelines to label input text consistently. The work also covered sentiment and intent labeling to support downstream AI behavior and quality checks. The annotations focused on maintaining high agreement with rules while improving accuracy over iterations. • Labeled text for sentiment and intent categories • Followed annotation guidelines to ensure consistency • Performed quality checks to maintain label accuracy • Refined labeling decisions based on observed errors

2023 - 2024

Education

Work History