Taofeeq A.

Key Skills

Software

AWS SageMaker

CVAT

Google Cloud Vertex AI

Label Studio

Prodigy

Roboflow

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Video

Top Task Types

Action Recognition

Bounding Box

Classification

Data Collection

Emotion Recognition

Entity (NER) Classification

Fine-tuning

Object Detection

Point/Key Point

Polygon

Prompt + Response Writing (SFT)

Segmentation

Transcription

Freelancer Overview

I am a certified entry-level AI Trainer and Prompt Engineer with hands-on experience in data annotation across computer vision and natural language processing domains. I have worked extensively with leading annotation tools such as CVAT, Prodigy, Roboflow, Azure, GCP, UDT, and AWS SageMaker Ground Truth, handling image, video, text, and audio data for tasks like object detection, segmentation, classification, sentiment analysis, and transcription. My background in project coordination has equipped me with strong attention to detail, guideline adherence, and the ability to maintain high accuracy and consistency in data labeling projects. I am adept at crafting and evaluating prompts for AI models, and I thrive in remote, collaborative environments where I can contribute to building high-quality training data for machine learning and generative AI systems.

Labeling Experience

Versatile Data Annotator

CVATImageObject Detection

I performed data annotation tasks focusing on images involving object detection and classification for machine learning applications. My work required using various computer vision tools such as CVAT, Roboflow, Azure, GCP, AWS SageMaker, and UDT. I ensured high-quality, consistent, and accurate labeling while adhering to project guidelines. • Labeled data using semantic and instance segmentation as well as object detection techniques. • Applied best practices across different cloud annotation platforms. • Ensured compliance with annotation protocols to maintain data integrity. • Collaborated with AI teams remotely to deliver annotated datasets on schedule.

I performed data annotation tasks focusing on images involving object detection and classification for machine learning applications. My work required using various computer vision tools such as CVAT, Roboflow, Azure, GCP, AWS SageMaker, and UDT. I ensured high-quality, consistent, and accurate labeling while adhering to project guidelines. • Labeled data using semantic and instance segmentation as well as object detection techniques. • Applied best practices across different cloud annotation platforms. • Ensured compliance with annotation protocols to maintain data integrity. • Collaborated with AI teams remotely to deliver annotated datasets on schedule.

Not specified

Image/Video Collection and Validation

Internal Proprietary ToolingVideoData Collection

Participated in an AI training data collection and validation project involving image and video content. The work focused on gathering and reviewing multimedia data to ensure it met defined quality, relevance, and labeling requirements for machine learning use. Tasks included validating submitted images and videos against project guidelines, checking clarity, completeness, and compliance, and rejecting or correcting content that did not meet standards. The project emphasized adaptability, consistency, and strict quality control to ensure the final dataset was accurate, diverse, and suitable for AI model training.

Participated in an AI training data collection and validation project involving image and video content. The work focused on gathering and reviewing multimedia data to ensure it met defined quality, relevance, and labeling requirements for machine learning use. Tasks included validating submitted images and videos against project guidelines, checking clarity, completeness, and compliance, and rejecting or correcting content that did not meet standards. The project emphasized adaptability, consistency, and strict quality control to ensure the final dataset was accurate, diverse, and suitable for AI model training.

2025 - 2025

Data Processing Associate (Annotation)

AppenImageBounding BoxClassification

Worked as a Data Processing Associate on an AI annotation project supporting the development of machine learning systems. Responsibilities included completing mandatory task training and calibration, performing data annotation according to detailed guidelines, and reviewing annotations for accuracy and consistency. After meeting quality benchmarks during the practice phase, production tasks were completed on a daily basis. Quality assurance measures included guideline adherence, self-review, error correction, and consistency validation to meet project accuracy requirements.

Worked as a Data Processing Associate on an AI annotation project supporting the development of machine learning systems. Responsibilities included completing mandatory task training and calibration, performing data annotation according to detailed guidelines, and reviewing annotations for accuracy and consistency. After meeting quality benchmarks during the practice phase, production tasks were completed on a daily basis. Quality assurance measures included guideline adherence, self-review, error correction, and consistency validation to meet project accuracy requirements.

2025 - 2025

Education

Work History