Machine Learning Quality Assurance

Skills

Summary

Education

Experience

Efficient anddetail-oriented Data Annotator with 2 years of experience in labeling and categorizing data for machine learning models and AI systems. Proficient in using various annotation tools and ensuring data quality through meticulous attention to detail. Experienced in quality assurance, collaborative problem-solving, and maintaining detailed documentation to support machine learning projects. Skilled in adapting to new technologies to meet project requirementsandimprove annotation processes.

MADHANKUMAR P

DATA ANNOTATOR

***********************@*****.*** 882-***-****

BE Civil Engineering 2019-2023

CGPA: 7.86

Final Year Project:

Experimental study on effect of partial replacement of waste aggregate by over burnt brick in concrete

Objectways Technology

Computer Vision and Data Labeling

2023-OCT2025

Senior Analyst

Annotated various types of data including text, images, audio, and video to machine learning models.

Applied appropriate tags and labels to datasets by specific guidelines and criteria. Ensured the accuracy and consistency of annotations by performing regular quality checks. Collaborated with team members to refine annotation guidelines and improve data quality. Adapted quickly to new tools and technologies for efficient data annotation. Participated in team meetings to discuss progress, challenges, and updates on annotation tasks. Identified areas for process improvements and implemented strategies to enhance annotation efficiency and accuracy.

Managed annotation projects simultaneously, ensuring timely delivery of high-quality annotated data.

Reviewed and corrected annotations made by other team members to ensure high data quality. Project Overview

KSR College of Engineering

LIDAR

Computer Vision

Image Annotation

AWS (Amazon Sagemaker Ground Truth)

GIS

Segment.ai

MS Excel

Adobe Photoshop

Communication:

English, Tamil

Tool Proficiency: gained experience with annotation tools such as AWS (Amazon Sagemaker Ground Truth), CVAT, ISEE(LATTE). Quality Assurance: Conducted quality checks on annotated data to ensure accuracy and consistency improving model performance by 93% in labeling the various elements within image, video, audio, text or data NLP and CV, Machine learning. Data labeling for large language models: image captioning, summarization, creative content, Geographic information system (GIS)

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