Fajar Mustafa

Key Skills

Software

CVAT

Other

Label Studio

Clickworker

Dataturk

Labelbox

Remotasks

iMerit

Internal/Proprietary Tooling

Top Subject Matter

Traffic Safety AI – Video Annotation

Restaraunt industry – Text and Audio Annotation

General Computer Vision – Image Annotation

Top Data Types

Video

Image

Text

Top Task Types

Object Detection

Bounding Box

Entity (NER) Classification

Classification

Polygon

Segmentation

Point/Key Point

RLHF

Transcription

Text Generation

Freelancer Overview

Data Annotation Specialist with 5+ years of experience delivering high-quality training data for AI systems across computer vision, NLP, and conversational AI. My expertise spans: 🔹 Computer Vision — bounding box, polygon, segmentation, keypoint, object detection, video annotation 🔹 NLP — NER, entity recognition, intent classification, sentiment analysis, relation extraction, entity clustering 🔹 Tools — CVAT, Label Studio, Labelbox, Darwin, Labelme, Encode, Moonvalley AI platform 🔹 QA & Documentation — SOPs, annotation guidelines, tool manuals, performance tracking 🔹 Leadership — team management, workflow coordination, cross-functional collaboration I care about understanding not just how to annotate but why—because clean, well-structured training data is what makes AI models actually work.

Labeling Experience

Data Annotation Specialist – Trials Team (Obvio AI)

CVATVideoObject Detection

Oversaw the full annotation and delivery pipeline for client trial video data in traffic safety AI projects. Performed scene calibration, event extraction, annotation, privacy blurring, and visualization using Retool and CVAT. Delivered high-quality, client-ready video datasets to stakeholders on schedule. • Coordinated team of annotators and managed cross-functional delivery. • Applied and maintained annotation guidelines and standards. • Ensured annotation integrity from ingestion to dataset handoff. • Produced documentation and onboarding resources in Notion.

Oversaw the full annotation and delivery pipeline for client trial video data in traffic safety AI projects. Performed scene calibration, event extraction, annotation, privacy blurring, and visualization using Retool and CVAT. Delivered high-quality, client-ready video datasets to stakeholders on schedule. • Coordinated team of annotators and managed cross-functional delivery. • Applied and maintained annotation guidelines and standards. • Ensured annotation integrity from ingestion to dataset handoff. • Produced documentation and onboarding resources in Notion.

2026 - Present

Video Data Annotator (Obvio AI)

CVATVideoObject Detection

Annotated traffic safety video footage in CVAT for computer vision model training programs. Labeled road events and objects, focusing on traffic signals, parking, and safety incidents. Assessed rejected license plate data, reviewed failure patterns, and aimed for continuous improvement. • Labeled objects and events in street-scene video. • Collaborated with team on AI performance analysis. • Tracked quality using internal dashboards. • Enhanced recognition accuracy for license plate datasets.

Annotated traffic safety video footage in CVAT for computer vision model training programs. Labeled road events and objects, focusing on traffic signals, parking, and safety incidents. Assessed rejected license plate data, reviewed failure patterns, and aimed for continuous improvement. • Labeled objects and events in street-scene video. • Collaborated with team on AI performance analysis. • Tracked quality using internal dashboards. • Enhanced recognition accuracy for license plate datasets.

2025 - 2026

Image Data Annotator – Team Lead (Moon Valley AI)

OtherImageBounding Box

Led a contractual image annotation team delivering bounding box and image captioning tasks for large-scale datasets. Supervised quality assurance processes across multiple annotators to ensure accuracy and consistency. Distributed tasks, provided feedback, and reviewed annotations before submission. • Tracked team progress with Excel-based tools. • Standardized project labeling to meet client specs. • Enforced accuracy through regular checks and corrections. • Delivered on time for contractual obligations.

Led a contractual image annotation team delivering bounding box and image captioning tasks for large-scale datasets. Supervised quality assurance processes across multiple annotators to ensure accuracy and consistency. Distributed tasks, provided feedback, and reviewed annotations before submission. • Tracked team progress with Excel-based tools. • Standardized project labeling to meet client specs. • Enforced accuracy through regular checks and corrections. • Delivered on time for contractual obligations.

2024 - 2025

Text Data Annotator (Ezra AI)

Label StudioTextEntity Ner Classification

Annotated text datasets for conversational AI models with a focus on NLP applications. Executed Named Entity Recognition, intent classification, sentiment analysis, and entity clustering on diverse projects. Used Label Studio to contribute high-quality labeled data for machine learning training. • Identified and labeled speakers, entities, and inter-entity relations. • Performed classification on both single utterance and multi-turn conversations. • Supported AI/ML teams with annotated datasets. • Managed multiple projects and schemas concurrently with Label Studio.

Annotated text datasets for conversational AI models with a focus on NLP applications. Executed Named Entity Recognition, intent classification, sentiment analysis, and entity clustering on diverse projects. Used Label Studio to contribute high-quality labeled data for machine learning training. • Identified and labeled speakers, entities, and inter-entity relations. • Performed classification on both single utterance and multi-turn conversations. • Supported AI/ML teams with annotated datasets. • Managed multiple projects and schemas concurrently with Label Studio.

2023 - 2024

Image Data Annotator (Remotasker)

RemotasksImageBounding Box

Annotated large volumes of street-scene images focused on vehicles, road objects, and traffic signals for self-driving datasets. Applied bounding boxes, polygons, and classification tags in support of object detection models. Maintained alignment with client-defined labeling taxonomies to ensure consistency. • Completed image batches according to established schemas. • Focused on annotation for automotive and traffic management applications. • Ensured high accuracy and quality through client feedback cycles. • Contributed data supporting AI models for traffic safety.

Annotated large volumes of street-scene images focused on vehicles, road objects, and traffic signals for self-driving datasets. Applied bounding boxes, polygons, and classification tags in support of object detection models. Maintained alignment with client-defined labeling taxonomies to ensure consistency. • Completed image batches according to established schemas. • Focused on annotation for automotive and traffic management applications. • Ensured high accuracy and quality through client feedback cycles. • Contributed data supporting AI models for traffic safety.

2022 - 2023

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Education

Work History