Guddu Pal

Key Skills

Software

Label Studio

Top Subject Matter

Conversational AI/NLP

Large Language Model Evaluation

Speech Recognition/ASR

Top Data Types

Text

Audio

Image

Top Task Types

Entity (NER) Classification

RLHF

Audio Recording

Text Generation

Transcription

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Text Summarization

Computer Programming/Coding

Object Detection

Question Answering

Freelancer Overview

AI Data Annotator & Tele-Operations Executive. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, Internal, and Proprietary Tooling. Education includes Bachelor of Arts, IGNOU (2024) and Diploma in Engineering, Siliguri Government Polytechnic (2023). AI-training focus includes data types such as Text and Audio and labeling workflows including Entity (NER) Classification, RLHF, and Audio Recording.

Labeling Experience

Audio Data Collector & Transcriber

Label StudioAudioAudio Recording

I collected, recorded, and transcribed audio samples in Bengali and Hindi for automated speech recognition model training. Tasks included high-quality recording, careful proofreading, and accurate time-stamped transcription in line with ASR guidelines. Challenges related to dialect and pronunciation were resolved in collaboration with project leads. • Contributed over 500 curated audio samples to speech datasets. • Focused on clean transcriptions and timely, accurate timestamping. • Quality reviewed all files to ensure usability for ML models. • Used Label Studio and internal tools for audio data processing.

I collected, recorded, and transcribed audio samples in Bengali and Hindi for automated speech recognition model training. Tasks included high-quality recording, careful proofreading, and accurate time-stamped transcription in line with ASR guidelines. Challenges related to dialect and pronunciation were resolved in collaboration with project leads. • Contributed over 500 curated audio samples to speech datasets. • Focused on clean transcriptions and timely, accurate timestamping. • Quality reviewed all files to ensure usability for ML models. • Used Label Studio and internal tools for audio data processing.

2024 - Present

AI Response Quality Evaluator (RLHF Human Annotation)

TextRLHF

I evaluated and ranked AI-generated text responses as part of the RLHF (Reinforcement Learning from Human Feedback) workflow. Structured written feedback was provided to highlight model strengths and areas for improvement, guiding LLM fine-tuning. Each week, I processed over 200 evaluation tasks while maintaining alignment with team calibration standards. • Focused on response accuracy, tone, safety, and helpfulness. • Contributed to improvements in production AI language models. • Used internal proprietary tools and feedback platforms for evaluation. • Maintained consistent rating calibration with the team.

I evaluated and ranked AI-generated text responses as part of the RLHF (Reinforcement Learning from Human Feedback) workflow. Structured written feedback was provided to highlight model strengths and areas for improvement, guiding LLM fine-tuning. Each week, I processed over 200 evaluation tasks while maintaining alignment with team calibration standards. • Focused on response accuracy, tone, safety, and helpfulness. • Contributed to improvements in production AI language models. • Used internal proprietary tools and feedback platforms for evaluation. • Maintained consistent rating calibration with the team.

2024 - Present

AI Data Annotator & Tele-Operations Executive

Label StudioTextEntity Ner Classification

As an AI Data Annotator, I annotated, classified, and labeled large volumes of text data for NLP and machine learning model training. I performed multilingual text labeling, including intent classification, sentiment analysis, and named entity recognition (NER) across English, Hindi, and Bengali datasets. The process followed strict annotation guidelines and schema documentation to ensure quality and consistency. • Labeled 10,000+ conversational utterances for an AI chatbot project. • Maintained quality benchmarks above 96% and personal error rate below 3%. • Participated in team adjudication sessions for complex edge cases. • Used Appen, Remotasks-style, and Label Studio platforms for annotation.

As an AI Data Annotator, I annotated, classified, and labeled large volumes of text data for NLP and machine learning model training. I performed multilingual text labeling, including intent classification, sentiment analysis, and named entity recognition (NER) across English, Hindi, and Bengali datasets. The process followed strict annotation guidelines and schema documentation to ensure quality and consistency. • Labeled 10,000+ conversational utterances for an AI chatbot project. • Maintained quality benchmarks above 96% and personal error rate below 3%. • Participated in team adjudication sessions for complex edge cases. • Used Appen, Remotasks-style, and Label Studio platforms for annotation.

2024 - Present

Education

Work History