John Waithera

Key Skills

Software

iMerit

Other

Top Subject Matter

Multimodal AI visual data (object, people, scene, actions, emotions)

Computer Vision

Video Content Analysis

Top Data Types

Image

Video

Top Task Types

Classification

Action Recognition

Freelancer Overview

Independent Consultant – Image & Video Annotation. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include iMerit and Other. Education includes Certificate, Tracom College and N/A, University of Nairobi. AI-training focus includes data types such as Image and Video and labeling workflows including Classification and Action Recognition.

Labeling Experience

Independent Consultant – Image & Video Annotation

ImeritImageClassification

As an independent consultant at iMerit, I annotated and analyzed large volumes of images and video clips for the training of multimodal AI and machine learning models. My main tasks included labeling visual cues such as objects, people, environments, actions, and emotions, as well as describing temporal sequences within media data. I contributed to structured datasets, validated AI-generated outputs, and followed strict annotation protocols to ensure data quality. • Labeled complex visual elements, spatial relationships, and emotional context in both images and videos. • Described scene transitions and motion patterns in video data with accuracy and consistency. • Collaborated on quality benchmarks and protocol evolution for AI visual reasoning improvements. • Leveraged annotation platforms and workflows to maintain data integrity and consistency.

As an independent consultant at iMerit, I annotated and analyzed large volumes of images and video clips for the training of multimodal AI and machine learning models. My main tasks included labeling visual cues such as objects, people, environments, actions, and emotions, as well as describing temporal sequences within media data. I contributed to structured datasets, validated AI-generated outputs, and followed strict annotation protocols to ensure data quality. • Labeled complex visual elements, spatial relationships, and emotional context in both images and videos. • Described scene transitions and motion patterns in video data with accuracy and consistency. • Collaborated on quality benchmarks and protocol evolution for AI visual reasoning improvements. • Leveraged annotation platforms and workflows to maintain data integrity and consistency.

2025 - Present

Video Annotation Specialist

OtherVideoAction Recognition

As a Video Annotation Specialist at Atlas Capture, I reviewed and annotated short video clips for computer vision and AI training datasets. My work focused on capturing subjects, settings, actions, narrative flow, and emotional nuances within the content. I ensured high annotation throughput while consistently meeting strict quality and accuracy benchmarks. • Applied detailed guidelines to tag mood, lighting, camera angles, and context in video scenes. • Documented scene transitions, object movements, and temporal interactions with precision. • Identified ambiguous or edge-case footage for supervised review and resolution. • Delivered clean and reliable data outputs for downstream AI model training purposes.

As a Video Annotation Specialist at Atlas Capture, I reviewed and annotated short video clips for computer vision and AI training datasets. My work focused on capturing subjects, settings, actions, narrative flow, and emotional nuances within the content. I ensured high annotation throughput while consistently meeting strict quality and accuracy benchmarks. • Applied detailed guidelines to tag mood, lighting, camera angles, and context in video scenes. • Documented scene transitions, object movements, and temporal interactions with precision. • Identified ambiguous or edge-case footage for supervised review and resolution. • Delivered clean and reliable data outputs for downstream AI model training purposes.

2025 - 2025

Education

Work History