Archit Kumar Awasthi

Key Skills

Software

Data Annotation Tech

Remotasks

Scale AI

Mindrift

Top Subject Matter

Llm Domain Expertise

Generative AI

Nlp Domain Expertise

Top Data Types

Text

Image

Top Task Types

Classification

RLHF

Evaluation/Rating

Freelancer Overview

AI Trainer (Freelance). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mindrift and Scale AI. Education includes Bachelor of Technology, Noida Institute of Engineering and Technology (2024) and Senior Secondary and Higher Secondary School Certificate, Pt. Deendayal Upadhyay Saraswati Vidya Mandir Inter College (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Trainer (Freelance)

MindriftText

As an AI Trainer (Freelance) at Mindrift AI, I developed and refined high-quality prompts to train large language models (LLMs). My work involved detailed evaluation and structured feedback on model outputs to enhance accuracy and contextual understanding. I contributed to dataset quality through annotation and curation aligned with project guidelines. • Conducted prompt engineering and iterative LLM training • Evaluated LLM outputs for tasks including summarization and question answering • Identified edge cases and failure patterns to improve model robustness • Reviewed, annotated, and curated text datasets according to use-case requirements

As an AI Trainer (Freelance) at Mindrift AI, I developed and refined high-quality prompts to train large language models (LLMs). My work involved detailed evaluation and structured feedback on model outputs to enhance accuracy and contextual understanding. I contributed to dataset quality through annotation and curation aligned with project guidelines. • Conducted prompt engineering and iterative LLM training • Evaluated LLM outputs for tasks including summarization and question answering • Identified edge cases and failure patterns to improve model robustness • Reviewed, annotated, and curated text datasets according to use-case requirements

2026 - Present

AI Trainer (Freelance)

Scale AIText

As an AI Trainer at Outlier AI (Scale AI), I contributed to the training and evaluation of large language models through high-quality prompt creation and response validation. My responsibilities included designing diverse datasets, including edge cases, to strengthen model performance and reduce hallucinations. I also participated in image classification tasks and visual question answering for AI model development. • Created and curated text prompts and validation scenarios for LLMs • Analyzed and annotated images for visual AI tasks • Supported model evaluation and iterative improvement • Collaborated with teams to ensure adherence to quality benchmarks

As an AI Trainer at Outlier AI (Scale AI), I contributed to the training and evaluation of large language models through high-quality prompt creation and response validation. My responsibilities included designing diverse datasets, including edge cases, to strengthen model performance and reduce hallucinations. I also participated in image classification tasks and visual question answering for AI model development. • Created and curated text prompts and validation scenarios for LLMs • Analyzed and annotated images for visual AI tasks • Supported model evaluation and iterative improvement • Collaborated with teams to ensure adherence to quality benchmarks

2025 - 2026

LLM Response Evaluation & Text Classification for AI Model Training

Data Annotation TechTextClassificationRLHF

The project included evaluating AI-generated responses for relevance, factual accuracy, coherence, safety, and instruction-following quality. Performed pairwise comparison tasks to rank model outputs and provided detailed reasoning to support evaluation decisions as part of RLHF (Reinforcement Learning from Human Feedback) workflows. Additionally, completed large-scale text classification tasks including sentiment analysis, topic categorization, and intent labeling across diverse datasets. Ensured strict adherence to annotation guidelines and maintained consistency across thousands of data points.

The project included evaluating AI-generated responses for relevance, factual accuracy, coherence, safety, and instruction-following quality. Performed pairwise comparison tasks to rank model outputs and provided detailed reasoning to support evaluation decisions as part of RLHF (Reinforcement Learning from Human Feedback) workflows. Additionally, completed large-scale text classification tasks including sentiment analysis, topic categorization, and intent labeling across diverse datasets. Ensured strict adherence to annotation guidelines and maintained consistency across thousands of data points.

2024 - 2025

Education

Work History