Rama Maruboina

Key Skills

Software

Label Studio

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Computer Code Programming

Image

Text

Top Label Types

Entity Ner Classification

Evaluation Rating

Mapping

RLHF

Freelancer Overview

I am a detail-oriented AI data labeling and annotation specialist with 7 years of experience supporting machine learning teams in preparing high-quality training datasets. My expertise spans labeling and validating text, image, audio, and structured data for a range of AI applications, including NLP tasks like sentiment analysis and entity recognition, as well as computer vision projects involving image classification, object detection, bounding boxes, and segmentation. I am skilled in using various annotation tools and platforms, conducting rigorous quality audits, and ensuring dataset consistency and accuracy through careful validation and review. My background in supporting AI model training pipelines and collaborating closely with engineers has given me a strong understanding of end-to-end AI workflows and the importance of reliable, clean data. I have contributed to large-scale dataset projects, optimized annotation processes, and am committed to delivering precise, production-ready data for high-impact AI solutions.

Labeling Experience

AI Training & Data Annotation Specialist (Freelance/Contract)

Label StudioTextEntity Ner Classification

As an AI Training & Data Annotation Specialist (Freelance/Contract), I performed high-volume data labeling for diverse AI/ML projects. My primary responsibilities included annotating text, image, and structured datasets, conducting data validation, and supporting model training pipelines. Quality assurance and adherence to annotation standards were integral parts of my workflow. • Annotated large-scale datasets for supervised learning, focusing on text, images, and structured data. • Conducted data validation, reviewed outputs, and corrected inconsistencies to ensure labeling accuracy. • Utilized various annotation tools and data labeling platforms as per project requirements. • Collaborated with AI engineers to improve the reliability and quality of training datasets.

As an AI Training & Data Annotation Specialist (Freelance/Contract), I performed high-volume data labeling for diverse AI/ML projects. My primary responsibilities included annotating text, image, and structured datasets, conducting data validation, and supporting model training pipelines. Quality assurance and adherence to annotation standards were integral parts of my workflow. • Annotated large-scale datasets for supervised learning, focusing on text, images, and structured data. • Conducted data validation, reviewed outputs, and corrected inconsistencies to ensure labeling accuracy. • Utilized various annotation tools and data labeling platforms as per project requirements. • Collaborated with AI engineers to improve the reliability and quality of training datasets.

2022

AI Support Engineer

Label StudioTextEntity Ner Classification

As an AI Support Engineer, I assisted AI teams with data labeling workflows and ensured high data quality for ML models. My tasks included supporting annotation pipeline automation and validating training data for deployment. The role demanded strong attention to data validation and process improvement. • Enhanced annotation accuracy and data quality metrics for AI model deployment. • Supported dataset preparation, label workflows, and pipeline automation. • Focused on quality assurance and efficient annotation processes. • Collaborated closely with multidisciplinary AI teams for continuous workflow improvement.

As an AI Support Engineer, I assisted AI teams with data labeling workflows and ensured high data quality for ML models. My tasks included supporting annotation pipeline automation and validating training data for deployment. The role demanded strong attention to data validation and process improvement. • Enhanced annotation accuracy and data quality metrics for AI model deployment. • Supported dataset preparation, label workflows, and pipeline automation. • Focused on quality assurance and efficient annotation processes. • Collaborated closely with multidisciplinary AI teams for continuous workflow improvement.

2020 - 2022

Education

Work History