Abhishek A.

Key Skills

Software

Other

AWS SageMaker

Anno-Mage

Appen

Axiom AI

Clickworker

CloudFactory

CrowdFlower

CrowdSource

Data Annotation Tech

Dataloop

Datatroniq

Datumbox

Datasaur

Deep Systems

Doccano

Top Subject Matter

LLM training datasets and AI model output validation

LLM output review and rule-based validation for AI systems

Top Data Types

Video

Image

Document

Top Task Types

RLHF

Polygon

Classification

Segmentation

Point/Key Point

Entity (NER) Classification

Text Generation

Text Summarization

Object Detection

Cuboid

Red Teaming

Fine-tuning

Question Answering

Data Collection

Function Calling

Computer Programming/Coding

Evaluation/Rating

Transcription

Prompt + Response Writing (SFT)

Freelancer Overview

AI Developer / AI Trainer / AI Annotation Specialist (AI-focused workflows, data annotation, structured review, output v. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N, A, and Other. Education includes Bachelor of Engineering, Visvesvaraya Technological University (2018) and Higher Secondary (12th), Kendriya Vidyalaya (2014). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

LLM Output Validation and Review; API and Automation Validation (supporting AI-enabled platform QA)

Other

Performed AI/LLM-oriented evaluation by assessing generated responses for completeness and expected behavior. Implemented rule-based validation and preprocessing support using Python and SQL to improve reliability of training and evaluation workflows. Applied API testing and validation practices to verify structured responses and payload correctness in AI-enabled systems. • Checked response structure, consistency, and adherence to instructions • Applied validation logic and schema checks • Verified request/response behavior and status codes • Supported automation-oriented QA for AI backend services

Not specified

AI Developer / AI Trainer / AI Annotation Specialist (AI-focused workflows, data annotation, structured review, output validation, prompt refinement)

TextRLHF

Provided AI training support by performing structured annotation, classification, and content review to improve consistency and machine-ready datasets. Reviewed model outputs for correctness, relevance, formatting, and instruction adherence to support evaluation-style feedback loops. Refined prompts and validation logic while performing quality checks to reduce data and workflow defects. • Labeled and categorized training data per guidelines • Conducted consistency checks and issue reporting for quality • Performed relevance/correctness/instruction adherence checks on outputs • Created validation approaches for response structure and expected behavior

Not specified

Education

Work History