Rentus M.

Key Skills

Software

Labelbox

Sama

Label Studio

Roboflow

Toloka

Top Subject Matter

Computer Vision and NLP

Data Quality Assurance (QA)

Road/Infrastructure Defect Detection

Top Data Types

Image

Text

3D Sensor

Document

Top Task Types

Classification

Segmentation

Cuboid

Bounding Box

Freelancer Overview

Data Annotator — AfricaAI Labs. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, Sama, and Label Studio. Education includes Bachelor of Science, University of Oxford (2018). AI-training focus includes data types such as Image, Text, and 3D Sensor and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

AVRIDE 3D Sensor Annotation Project

Toloka3D SensorCuboid

Performed 3D sensor data annotation for unannotated objects in autonomous-systems datasets. Labeled segments and cuboids to create structured training data suitable for AI models. Ensured high-quality 3D annotations through careful review to support reliable model performance. • Segmented 3D sensor data • Created cuboid labels for objects • Prepared training-ready labels for AI systems • Conducted quality-focused annotation validation

2024 - Present

GRAPES Image Annotation Project

RoboflowImageClassification

Annotated images of grapes to classify ripe versus unripe fruit for ML model development. Produced 20,000 high-quality labeled images by applying consistent labeling practices and iterative quality checks. Ensured data accuracy and consistency to support agricultural analysis and fruit quality detection models. • Labeled grape images for ripeness classification • Generated 20,000 labeled images over the project period • Applied meticulous quality checks for consistency • Supported development of agriculture-focused ML models

2024 - 2024

Data Analyst Intern — Samasource

SamaText

Supported QA-oriented data preparation by cleaning, validating, and analyzing datasets used for project quality reviews. Helped design test cases and document results to support accurate assessment of data and workflows. Tracked project metrics and contributed to automation testing and reporting to improve data processing efficiency. • Performed data cleaning and validation • Authored QA test cases and documented outcomes • Analyzed test outputs and suggested workflow improvements • Tracked project metrics for efficient processing

2021 - 2024

Prenav Image Segmentation Project

Label StudioImageSegmentation

Performed image segmentation labeling to identify and label cracks on high-resolution images. Applied polygons and keypoints, using bounding boxes where needed, to ensure precise and consistent annotations. Ensured annotation accuracy and adherence to project labeling standards for downstream ML model development. • Segmented cracks in high-resolution images • Used polygon annotations and keypoint labeling • Applied bounding boxes for additional localization • Maintained precision and consistency via quality checks

2021 - 2021

CDI 38 Autonomous Vehicle Annotation Project

ImageBounding Box

Annotated vehicles, pedestrians, and other objects for a self-driving dataset intended for ML training. Produced accurate bounding-style annotations that supported high-performing model outcomes. Achieved 99% model accuracy through attention to annotation detail and dataset correctness. • Labeled vehicles and pedestrians • Annotated objects for autonomous driving datasets • Ensured correct object representation in labels • Supported 99% model accuracy through quality work

2020 - 2021

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Education

Work History