Shubham Wankhade

Key Skills

Software

Appen

Clickworker

Data Annotation Tech

Humanatic

LabelImg

Labelbox

OneForma

Micro1

Mindrift

Remotasks

Toloka

Telus

Surge AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Computer Code Programming

Image

Top Label Types

RLHF

Computer Programming Coding

Prompt Response Writing SFT

Diagnosis

Text Generation

Text Summarization

Fine Tuning

Question Answering

Evaluation Rating

Data Collection

Function Calling

Transcription

Point Key Point

Freelancer Overview

I am a software engineer with hands-on experience in building AI-powered solutions and developing applications that rely heavily on high-quality training data. My background includes working with Natural Language Processing (NLP), computer vision, and machine learning across projects such as AI-powered code assistants, smart college management systems, and cloud-based hotel reservation platforms. I have practical knowledge of data annotation and labeling workflows, having implemented features like attendance tracking using computer vision AI and chatbots powered by NLP models. My expertise spans Python, TensorFlow, PyTorch, FastAPI, and OpenAI API, enabling me to design, process, and validate datasets for robust AI model training. I am passionate about ensuring data quality and optimizing AI systems for real-world applications in domains like education, travel, and metaverse environments.

Labeling Experience

Prompt response review

Scale AITextRLHFComputer Programming Coding

The Prompt Response Review project focused on evaluating and labeling large-scale text datasets generated from AI model responses in the domain of computer programming. The primary objective was to enhance model alignment, instruction-following capabilities, and response quality through Reinforcement Learning from Human Feedback (RLHF) and Supervised Fine-Tuning (SFT) tasks. The project involved critical assessment of AI responses to technical prompts related to programming, debugging, code review, and logical reasoning.

The Prompt Response Review project focused on evaluating and labeling large-scale text datasets generated from AI model responses in the domain of computer programming. The primary objective was to enhance model alignment, instruction-following capabilities, and response quality through Reinforcement Learning from Human Feedback (RLHF) and Supervised Fine-Tuning (SFT) tasks. The project involved critical assessment of AI responses to technical prompts related to programming, debugging, code review, and logical reasoning.

2024 - 2025

Backend Developer

Scale AIComputer Code ProgrammingDiagnosisRLHF

Work experience in Travel & Hospitality domain and worked for global projects like Amadeus and TravelClick. • Work experience in metaverse project model for future cities NEOM. • Worked on Core project module ,Vital module for Travel & Hospitality functions ARI(i.e.Availability,Rate,Inventory) processing, Booking, Services & Promotions etc. • Developed REST Web Services with 360 degree prespective from documentation to final deployment • Handling client communication to understand project requirement and devise solutions accordingly. • Migrate applications from ANT to MAVEN • Migrate GDS and Meta applications to rest-to-ih-adapter to retire CA-Gateway.

Work experience in Travel & Hospitality domain and worked for global projects like Amadeus and TravelClick. • Work experience in metaverse project model for future cities NEOM. • Worked on Core project module ,Vital module for Travel & Hospitality functions ARI(i.e.Availability,Rate,Inventory) processing, Booking, Services & Promotions etc. • Developed REST Web Services with 360 degree prespective from documentation to final deployment • Handling client communication to understand project requirement and devise solutions accordingly. • Migrate applications from ANT to MAVEN • Migrate GDS and Meta applications to rest-to-ih-adapter to retire CA-Gateway.

2023 - 2025

Education

Work History