Tadiwanashe S Nziraindefu

Key Skills

Software

CVAT

Labelbox

LabelImg

Label Studio

V7 Labs

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Text

Top Label Types

Bounding Box

Polygon

Point Key Point

Polyline

Entity Ner Classification

Segmentation

Evaluation Rating

Transcription

Freelancer Overview

I am a detail-oriented data annotation specialist with over two years of experience delivering high-quality datasets for AI and machine learning projects, particularly in NLP/LLMs and computer vision domains. My expertise includes annotating and labeling text, images, and videos using tools such as CVAT, Label Studio, Labelbox, Prodigy, and V7 Labs, as well as working with LiDAR data. I have a strong track record of adhering to project guidelines, ensuring consistency, and meeting deadlines, while also performing quality assurance checks and mentoring teams to uphold data privacy and annotation standards. With a technical background in Python, OpenCV, and data processing, I am passionate about contributing to innovative AI solutions and continuously improving data quality for model training and evaluation.

Labeling Experience

AI/ML Training Data Specialist

Internal Proprietary ToolingTextEvaluation RatingTranscription

Working as an AI/ML Training Data Specialist at e2f, Inc. (Freelancer, Remote), contributing to the development and refinement of LLMs and NLP systems. Responsible for annotating, reviewing, and labeling text data for chatbot, translation, and text analysis applications. Applied strong linguistic understanding and strict adherence to annotation guidelines to ensure high-quality, consistent datasets that enhance model accuracy and performance. Collaborated with cross-functional AI teams to align data specifications with evaluation metrics and production requirements.

Working as an AI/ML Training Data Specialist at e2f, Inc. (Freelancer, Remote), contributing to the development and refinement of LLMs and NLP systems. Responsible for annotating, reviewing, and labeling text data for chatbot, translation, and text analysis applications. Applied strong linguistic understanding and strict adherence to annotation guidelines to ensure high-quality, consistent datasets that enhance model accuracy and performance. Collaborated with cross-functional AI teams to align data specifications with evaluation metrics and production requirements.

2024

Data Annotater

CVATVideoBounding BoxEntity Ner Classification

Worked as a sports data annotator with Sport AI, labelling tennis, padel, and related racket sport footage for AI model development. Responsibilities included annotating players, rackets, ball trajectories, court boundaries, and key actions using bounding boxes, polygons, and polylines. Maintained high precision and consistency by adhering to detailed annotation guidelines and performing regular quality control checks to ensure reliable training data for sports analytics models.

Worked as a sports data annotator with Sport AI, labelling tennis, padel, and related racket sport footage for AI model development. Responsibilities included annotating players, rackets, ball trajectories, court boundaries, and key actions using bounding boxes, polygons, and polylines. Maintained high precision and consistency by adhering to detailed annotation guidelines and performing regular quality control checks to ensure reliable training data for sports analytics models.

2024 - 2025

Quality Assurer (QA), Data Annotations

CVATImageBounding BoxPolygon

Worked as a quality assurer and data annotator at Talent Africa, labelling NFL sports footage and images for computer vision model training. Tasks included drawing precise bounding boxes, polygons, and polylines to annotate players, field markings, ball movement, and key in-game actions. Ensured high annotation accuracy by following strict labelling guidelines and performing quality checks to maintain consistency and reliability of the dataset.

Worked as a quality assurer and data annotator at Talent Africa, labelling NFL sports footage and images for computer vision model training. Tasks included drawing precise bounding boxes, polygons, and polylines to annotate players, field markings, ball movement, and key in-game actions. Ensured high annotation accuracy by following strict labelling guidelines and performing quality checks to maintain consistency and reliability of the dataset.

2023 - 2024

Education

Work History