Nisha Yadav

Key Skills

Software

Scale AI

Toloka

Other

Mindrift

Data Annotation Tech

Top Subject Matter

Artificial Intelligence

Machine Learning

Mathematics AI

Top Data Types

Text

Image

Document

Top Task Types

Classification

Bounding Box

Entity (NER) Classification

Object Detection

Text Generation

Question Answering

RLHF

Transcription

Prompt + Response Writing (SFT)

Evaluation/Rating

Segmentation

Freelancer Overview

Generalist AI Trainer. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Toloka, and DataAnnotation Tech. Education includes Master of Science, London School of Economics (2025) and Bachelor of Science, University of Delhi (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Trainer

TolokaTextClassification

As an AI Trainer for Toloka Annotators (Mindrift), I reviewed and annotated text, image, and video data to support machine learning projects. I followed detailed guidelines to ensure high accuracy and consistency. I evaluated model responses and flagged incorrect or sensitive content for quality assurance. • Annotated and classified multi-modal content. • Maintained rigorous standards for quality and consistency. • Used annotation platforms relevant to Toloka and Mindrift. • Collaborated on trust and safety data initiatives.

As an AI Trainer for Toloka Annotators (Mindrift), I reviewed and annotated text, image, and video data to support machine learning projects. I followed detailed guidelines to ensure high accuracy and consistency. I evaluated model responses and flagged incorrect or sensitive content for quality assurance. • Annotated and classified multi-modal content. • Maintained rigorous standards for quality and consistency. • Used annotation platforms relevant to Toloka and Mindrift. • Collaborated on trust and safety data initiatives.

2025 - Present

Generalist AI Trainer

Scale AIText

As a Generalist AI Trainer at Scale AI, I evaluated AI-generated outputs for accuracy and logical consistency. I analyzed model behavior, identified systematic errors, and designed structured prompts for reasoning assessment. I provided feedback to improve model reliability and worked with structured datasets to enhance data quality. • Assessed the correctness and quality of AI outputs. • Designed and tested prompts and problem sets to measure model competence. • Used Python and advanced data analysis techniques for evaluation. • Supported large-scale model improvement initiatives.

As a Generalist AI Trainer at Scale AI, I evaluated AI-generated outputs for accuracy and logical consistency. I analyzed model behavior, identified systematic errors, and designed structured prompts for reasoning assessment. I provided feedback to improve model reliability and worked with structured datasets to enhance data quality. • Assessed the correctness and quality of AI outputs. • Designed and tested prompts and problem sets to measure model competence. • Used Python and advanced data analysis techniques for evaluation. • Supported large-scale model improvement initiatives.

2025 - Present

Data Labeling Job Simulation

OtherTextClassification

In the Data Labeling Job Simulation at Forage, I practiced classifying messages for intent, sentiment, and personally identifiable information (PII). I reviewed labeling work for inconsistencies and suggested improvements. This experience provided hands-on exposure to foundational processes in human-AI collaboration. • Classified text data for multiple AI-relevant categories. • Improved quality control by checking and refining label accuracy. • Learned standard industry practices for data labeling workflow. • Applied feedback loops to simulate real-world annotation.

In the Data Labeling Job Simulation at Forage, I practiced classifying messages for intent, sentiment, and personally identifiable information (PII). I reviewed labeling work for inconsistencies and suggested improvements. This experience provided hands-on exposure to foundational processes in human-AI collaboration. • Classified text data for multiple AI-relevant categories. • Improved quality control by checking and refining label accuracy. • Learned standard industry practices for data labeling workflow. • Applied feedback loops to simulate real-world annotation.

2025 - 2025

Mathematics AI Trainer

Text

As a Mathematics AI Trainer at DataAnnotation, I assessed mathematical outputs from AI models for correctness and efficiency. I designed and evaluated complex mathematical problem sets to test reasoning. My evaluations contributed to model improvement through structured feedback. • Reviewed solutions to advanced mathematics problems generated by AI. • Tested the reasoning and logic skills of AI models. • Provided detailed reports to enhance model learning. • Used DataAnnotation tools for structured assessment and annotation.

As a Mathematics AI Trainer at DataAnnotation, I assessed mathematical outputs from AI models for correctness and efficiency. I designed and evaluated complex mathematical problem sets to test reasoning. My evaluations contributed to model improvement through structured feedback. • Reviewed solutions to advanced mathematics problems generated by AI. • Tested the reasoning and logic skills of AI models. • Provided detailed reports to enhance model learning. • Used DataAnnotation tools for structured assessment and annotation.

2025 - 2025

Education

Work History