Daniel Watatua

Key Skills

Software

CVAT

Supervisely

Mercor

Top Subject Matter

Autonomous Vehicles

Computer Vision

Autonomous Navigation

Top Data Types

Video

Image

Top Task Types

Bounding Box

Segmentation

Cuboid

Freelancer Overview

Freelance Data Annotator | Uber AI. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT, Supervisely, and Mercor. Education includes Bachelor of Science, University of Nairobi (2023). AI-training focus includes data types such as Video and Image and labeling workflows including Bounding Box, Segmentation, and Cuboid.

Labeling Experience

Freelance Data Annotator | Uber AI

CVATVideoBounding Box

I annotated large-scale video and image datasets for autonomous vehicle perception models, focusing on pedestrian, vehicle, and obstacle detection. I applied precise 2D and 3D bounding boxes across multi-frame video sequences to support object tracking and depth estimation. I performed LiDAR point cloud annotation, labeling 3D objects with high spatial accuracy to train self-driving vehicle models. • Maintained annotation accuracy above 98%, consistently meeting strict quality thresholds. • Used CVAT, Labelbox, Scale AI, and Supervisely to process annotation tasks. • Labeled vehicles, pedestrians, cyclists, and road infrastructure in diverse environments. • Supported the training and evaluation pipeline for autonomous systems.

I annotated large-scale video and image datasets for autonomous vehicle perception models, focusing on pedestrian, vehicle, and obstacle detection. I applied precise 2D and 3D bounding boxes across multi-frame video sequences to support object tracking and depth estimation. I performed LiDAR point cloud annotation, labeling 3D objects with high spatial accuracy to train self-driving vehicle models. • Maintained annotation accuracy above 98%, consistently meeting strict quality thresholds. • Used CVAT, Labelbox, Scale AI, and Supervisely to process annotation tasks. • Labeled vehicles, pedestrians, cyclists, and road infrastructure in diverse environments. • Supported the training and evaluation pipeline for autonomous systems.

2023 - Present

Data Annotation Specialist | ATLAS Capture

SuperviselyImageSegmentation

I annotated complex image and video datasets for computer vision applications, including semantic segmentation and polygon-based region labeling. I collaborated with other annotation specialists to ensure quality and uniform standards. I contributed to the accuracy and completeness of computer vision training data for autonomous systems. • Performed polygon and segmentation labeling in computer vision applications. • Handled dataset curation for urban and off-road scenarios. • Ensured consistent labeling with distributed teams. • Conducted quality assurance of annotation output.

I annotated complex image and video datasets for computer vision applications, including semantic segmentation and polygon-based region labeling. I collaborated with other annotation specialists to ensure quality and uniform standards. I contributed to the accuracy and completeness of computer vision training data for autonomous systems. • Performed polygon and segmentation labeling in computer vision applications. • Handled dataset curation for urban and off-road scenarios. • Ensured consistent labeling with distributed teams. • Conducted quality assurance of annotation output.

2023 - 2024

Data Annotator | Mecor

MercorImageCuboid

I delivered annotated training datasets for object detection and image classification models on multiple projects. I specialized in 3D object labeling for robotics and industrial automation, ensuring geometric precision. I utilized enterprise annotation platforms to efficiently manage and submit high volumes of labeled data. • Focused on geometric accuracy in cuboid 3D object labeling tasks. • Maintained high throughput for timely delivery of client datasets. • Contributed to process documentation to improve project onboarding. • Supported dataset quality assurance processes for industrial automation.

I delivered annotated training datasets for object detection and image classification models on multiple projects. I specialized in 3D object labeling for robotics and industrial automation, ensuring geometric precision. I utilized enterprise annotation platforms to efficiently manage and submit high volumes of labeled data. • Focused on geometric accuracy in cuboid 3D object labeling tasks. • Maintained high throughput for timely delivery of client datasets. • Contributed to process documentation to improve project onboarding. • Supported dataset quality assurance processes for industrial automation.

2022 - 2023

Education

Work History