Venkatasai Dasari

Key Skills

Software

Appen

Clickworker

Data Annotation Tech

HiveMind

Labelbox

Mercor

OneForma

Scale AI

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Geospatial Tiled Imagery

Image

Top Label Types

Audio Recording

Data Collection

Evaluation Rating

Object Detection

Translation Localization

Freelancer Overview

I have hands-on experience working with AI training data and programming-focused tasks, including text annotation, image labeling, and code evaluation for machine learning systems. With a background in software development (Python, JavaScript, APIs, and databases), I understand how high-quality training data impacts model performance. I have worked on tasks such as classifying text datasets, validating AI-generated responses, labeling images for object detection, and reviewing code outputs produced by AI systems. In addition to data annotation, I contribute from a technical perspective by evaluating programming-related outputs, identifying logical errors, and improving dataset quality for AI model training. My combined experience in software engineering and structured data labeling helps ensure accuracy, consistency, and useful training datasets for AI systems.

Labeling Experience

AI trainer

Computer Code ProgrammingFine Tuning

I worked on a application called cline where I will ask it prepare a fully functional prototype and it write code, document it, commit to GitHub and all the functions i oversaw it completion and code check.

I worked on a application called cline where I will ask it prepare a fully functional prototype and it write code, document it, commit to GitHub and all the functions i oversaw it completion and code check.

2024 - 2025

AI Training & Data Labeling for Generative AI Projects

AppenTextQuestion AnsweringText Generation

Contributed to multiple generative AI projects under Appen Crowd, focusing on text, image, and audio data labeling for model training and evaluation. Tasks included prompt–response writing for supervised fine-tuning (SFT), safety and quality evaluation of large language models, entity tagging, emotion/sentiment classification, and multimodal labeling (object detection and video action recognition). Ensured high accuracy through cross-check validation, adherence to detailed labeling guidelines, and quality assurance reviews. Worked on projects of varying scales, from small evaluation batches to large datasets with thousands of entries, supporting the improvement of AI models used in chatbots, autonomous systems, and generative applications.

Contributed to multiple generative AI projects under Appen Crowd, focusing on text, image, and audio data labeling for model training and evaluation. Tasks included prompt–response writing for supervised fine-tuning (SFT), safety and quality evaluation of large language models, entity tagging, emotion/sentiment classification, and multimodal labeling (object detection and video action recognition). Ensured high accuracy through cross-check validation, adherence to detailed labeling guidelines, and quality assurance reviews. Worked on projects of varying scales, from small evaluation batches to large datasets with thousands of entries, supporting the improvement of AI models used in chatbots, autonomous systems, and generative applications.

2021 - 2024

Education

Work History