Ravi Kant Kumar

Key Skills

Software

Appen

Data Annotation Tech

Google Cloud Vertex AI

Labelbox

Mindrift

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Image

Text

Top Label Types

Bounding Box

Computer Programming Coding

Entity Ner Classification

Evaluation Rating

Prompt Response Writing SFT

RLHF

Text Summarization

Transcription

Freelancer Overview

I am an experienced AI Data Specialist with over 3 years supporting AI model training, LLM evaluation, and high-precision data annotation. My work includes QA-style evaluations of large language model outputs for accuracy, safety, and compliance, as well as scenario and prompt design to rigorously test NLP models. I have a strong command of Python, SQL, and BI tools like Power BI, which I use to analyze and visualize large datasets, automate reporting, and improve decision-making processes. My background also covers statistical analysis, campaign performance optimization, and data-driven lead generation. I consistently deliver 99% accuracy in my annotation and evaluation tasks, and I thrive in collaborative, detail-oriented environments where data quality and integrity are paramount.

Labeling Experience

AI Specialist & QA Freelancer

Scale AITextRLHF

As an AI Specialist & QA Freelancer, conducted QA-style evaluations of large language model (LLM) outputs for accuracy, safety, and compliance. Designed structured scenarios and edge-case prompts to rigorously test model robustness and NLP dataset integrity. Performed high-precision annotation of NLP datasets and validated code-based responses through technical debugging methods. • Worked on reinforcement learning from human feedback (RLHF) for improved LLM output quality. • Designed and executed red teaming tasks and prompt engineering for edge-case testing. • Ensured deliverables maintained a 99% accuracy rate and followed strict compliance standards. • Utilized platforms such as Scale AI, Appen, Lionbridge, and Outlier for annotation and evaluation tasks.

As an AI Specialist & QA Freelancer, conducted QA-style evaluations of large language model (LLM) outputs for accuracy, safety, and compliance. Designed structured scenarios and edge-case prompts to rigorously test model robustness and NLP dataset integrity. Performed high-precision annotation of NLP datasets and validated code-based responses through technical debugging methods. • Worked on reinforcement learning from human feedback (RLHF) for improved LLM output quality. • Designed and executed red teaming tasks and prompt engineering for edge-case testing. • Ensured deliverables maintained a 99% accuracy rate and followed strict compliance standards. • Utilized platforms such as Scale AI, Appen, Lionbridge, and Outlier for annotation and evaluation tasks.

2023

Education

Work History