James Waweru

Key Skills

Software

Sama

Top Subject Matter

No subject matter listed

Top Data Types

Video

Top Label Types

Bounding Box

Polygon

Point Key Point

Segmentation

Emotion Recognition

Freelancer Overview

I am a motivated and detail-oriented professional with several years of experience in AI data labeling and annotation, primarily gained at Sama source. My background includes processing data through tagging, annotating, and capturing information using standard procedures to ensure high data quality and prevent duplication. I am skilled in using Microsoft Office applications, web research, and image annotation tools, and I consistently meet project deadlines while collaborating effectively with team members. I am committed to continuous improvement and thrive in fast-paced environments where accuracy and efficiency are essential. I am eager to contribute my skills to forward-thinking projects in AI training data, computer vision, or related domains.

Labeling Experience

Data Annotation Specialist

SamaVideoBounding BoxPolygon

Project Scope & Tasks The project focuses on high-precision "Human-in-the-Loop" (HITL) annotation for complex datasets across image, video, and 3D Point Cloud formats. Key tasks performed include: Object Detection & Classification: Identifying and tagging specific entities (e.g., people, doors, vehicles) within raw footage. Semantic & Instance Segmentation: Creating pixel-precise masks for every distinct object to train perception models. Advanced Tracking: Temporal annotation for video data to ensure consistent object identification across frames. Model Evaluation: Scoring real-world performance, including Reinforcement Learning from Human Feedback (RLHF) and hallucination detection for GenAI projects. 2. Project Size & Scalability Dataset Volume: Recent projects include annotating over 2.5 million product SKUs for global retail and millions of waste objects for visibility models.

Project Scope & Tasks The project focuses on high-precision "Human-in-the-Loop" (HITL) annotation for complex datasets across image, video, and 3D Point Cloud formats. Key tasks performed include: Object Detection & Classification: Identifying and tagging specific entities (e.g., people, doors, vehicles) within raw footage. Semantic & Instance Segmentation: Creating pixel-precise masks for every distinct object to train perception models. Advanced Tracking: Temporal annotation for video data to ensure consistent object identification across frames. Model Evaluation: Scoring real-world performance, including Reinforcement Learning from Human Feedback (RLHF) and hallucination detection for GenAI projects. 2. Project Size & Scalability Dataset Volume: Recent projects include annotating over 2.5 million product SKUs for global retail and millions of waste objects for visibility models.

2023 - 2024

Education

Work History