Nikita Soni

Key Skills

Software

Remotasks

iMerit

Appen

Data Annotation Tech

Top Subject Matter

Conversational AI

Large Language Models

Nlp Domain Expertise

Top Data Types

Text

Image

Video

Top Task Types

Prompt + Response Writing (SFT)

Classification

Evaluation/Rating

Question Answering

Object Detection

Bounding Box

RLHF

Freelancer Overview

AI Data Trainer & Prompt Engineer. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Remotasks and iMerit. Education includes Bachelor of Engineering, MBM University. AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT) and Classification.

Labeling Experience

AI Data Trainer & Prompt Engineer

RemotasksTextPrompt Response Writing SFT

• Designed, tested, and refined prompts to improve LLM response accuracy and relevance. • Evaluated AI-generated outputs against quality rubrics for accuracy, safety, and tone. • Annotated and structured datasets for NLP and conversational AI model training. • Provided feedback to enhance model performance through iterative testing and prompt optimization. • Performed quality assurance on datasets and AI outputs to ensure high standards of data integrity

• Designed, tested, and refined prompts to improve LLM response accuracy and relevance. • Evaluated AI-generated outputs against quality rubrics for accuracy, safety, and tone. • Annotated and structured datasets for NLP and conversational AI model training. • Provided feedback to enhance model performance through iterative testing and prompt optimization. • Performed quality assurance on datasets and AI outputs to ensure high standards of data integrity

2024 - Present

AI Data Annotator

ImeritTextClassification

• Labelled and categorized large-scale datasets to support machine learning and NLP model development. • Evaluated prompt–response pairs to improve LLM accuracy, consistency, and contextual understanding. • Contributed to the creation of high-quality datasets for AI training and evaluation tasks. • Ensured data integrity by applying rigorous, multi-level quality checks and validation processes.

• Labelled and categorized large-scale datasets to support machine learning and NLP model development. • Evaluated prompt–response pairs to improve LLM accuracy, consistency, and contextual understanding. • Contributed to the creation of high-quality datasets for AI training and evaluation tasks. • Ensured data integrity by applying rigorous, multi-level quality checks and validation processes.

2023 - 2023

Education

Work History