Anass Okhita

Key Skills

Software

CVAT

Other

Roboflow

OpenCV AI Kit (OAK)

Label Studio

LabelImg

Top Subject Matter

Industrial defect detection and quality assurance

Semantic structuring of technical documentation for AI applications

Top Data Types

Image

Text

Computer Code Programming

Top Task Types

Bounding Box

Classification

Segmentation

Object Detection

Text Generation

Question Answering

Text Summarization

RLHF

Fine Tuning

Transcription

Evaluation Rating

Computer Programming Coding

Data Collection

Freelancer Overview

Industrial Quality Dataset Curation & Labeling – Deep Learning Defect Detection (PREMO). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include LabelImg, CVAT, and Roboflow. Education includes State Engineering Degree, ENSA Tangier (National School of Applied Sciences) (2024) and Preparatory Classes for Grandes Écoles, Classes Préparatoires aux Grandes Écoles (CPGE) (2020). AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box and Classification.

Labeling Experience

Semantic Data Structuring for RAG Systems – AI Agent Orchestration Project Lead

TextClassification

Labeled and structured large-scale technical documentation for Retrieval-Augmented Generation (RAG) AI Agents. Converted unstructured technical data into clean JSON formats for improved information retrieval by language models. Mapped complex data flows and maintained semantic data integrity for downstream AI applications. • Processed technical documents for RAG systems • Enhanced LLM retrieval with structured JSON • Managed data mappings between webhooks and CRM tools • Led semantic structuring for AI orchestration

Labeled and structured large-scale technical documentation for Retrieval-Augmented Generation (RAG) AI Agents. Converted unstructured technical data into clean JSON formats for improved information retrieval by language models. Mapped complex data flows and maintained semantic data integrity for downstream AI applications. • Processed technical documents for RAG systems • Enhanced LLM retrieval with structured JSON • Managed data mappings between webhooks and CRM tools • Led semantic structuring for AI orchestration

2025 - 2025

Industrial Quality Dataset Curation & Labeling – Deep Learning Defect Detection (PREMO)

LabelimgImageBounding Box

Curated a dataset of over 5,000 industrial images for defect detection using high-precision image labeling. Performed annotation with bounding boxes and segmentation to train computer vision neural networks. Implemented quality assurance protocols for label consistency to optimize model performance. • Custom dataset developed for CNN-based defect detection • High-precision annotation for robust AI model training • Quality Assurance (QA) process established • Contributed to significant improvement in model F1-score

Curated a dataset of over 5,000 industrial images for defect detection using high-precision image labeling. Performed annotation with bounding boxes and segmentation to train computer vision neural networks. Implemented quality assurance protocols for label consistency to optimize model performance. • Custom dataset developed for CNN-based defect detection • High-precision annotation for robust AI model training • Quality Assurance (QA) process established • Contributed to significant improvement in model F1-score

2024 - 2024

Education

Work History