Kalpani G.

Key Skills

Software

Other

Top Subject Matter

LLM

Reasoning Based AI training

Top Data Types

Image

Video

Text

Top Task Types

Bounding Box

Evaluation/Rating

Object Detection

Freelancer Overview

I have hands-on experience in AI training data creation, annotation, prompt writing, and AI model evaluation through my work as an AI Trainer for Innodata (Meta Platforms project). I completed over 1,500 AI evaluation and prompt-based tasks, assessing and ranking LLM-generated responses for accuracy, relevance, instruction following, and policy compliance. My experience spans multimodal AI workflows, including text, image, and video annotation, where I identified model failure cases, perception errors, ambiguities, and data quality issues while maintaining consistent guideline adherence and structured decision-making. What sets me apart is my combination of AI evaluation expertise and over 10 years of software engineering experience. I have strong analytical and problem-solving skills, extensive experience working with complex technical systems, and a deep understanding of quality assurance processes. My background includes prompt design, LLM response evaluation, content moderation, multimodal annotation, and rule-based decision making, enabling me to contribute effectively to high-quality AI training data development and model improvement initiatives.

Labeling Experience

Independent Contractor

ImageEvaluation/Rating

As an AI Trainer for Innodata (Meta Platforms project), I worked on large-scale AI training data and model evaluation projects involving text, image, audio and video data. My responsibilities included prompt writing, LLM response evaluation and ranking, multimodal annotation, perception tasks, content understanding, and quality assessment. I completed over 1,500 AI evaluation and annotation tasks, covering object detection, dense bounding boxes, referring expression grounding, image quality comparison, video annotation, and model behavior testing across diverse scenarios and edge cases. Quality was maintained through strict adherence to detailed annotation guidelines, policy compliance requirements, and QA review processes. My work involved identifying ambiguities, perception errors, and model failure cases, providing structured feedback, and ensuring consistency and accuracy in annotations and evaluations. I maintained a strong QA rating while working in a high-volume production environment, demonstrating attention to detail, analytical reasoning, and reliable decision-making.

2026 - 2026

Education

Work History