Marklewis M.

Key Skills

Software

CVAT

Label Studio

Other

Top Subject Matter

Computer vision for reinforcement learning and machine learning dataset training

NLP labeling for text classification

intent mapping

Top Data Types

Image

Text

Document

Top Task Types

Object Detection

Entity (NER) Classification

Data Collection

Freelancer Overview

Data Annotation & AI Training Specialist (Freelance/Remote Technical Consultant) — computer vision annotation and qualit. Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include CVAT, Label Studio, and Other. AI-training focus includes data types such as Image and Text and labeling workflows including Object Detection, Entity (NER) Classification, and Data Collection.

Labeling Experience

Data Annotation & AI Training Specialist (Freelance/Remote Technical Consultant) — NLP annotation and validation

Label StudioTextEntity (NER) Classification

Executed complex NLP labeling tasks to prepare high-fidelity training data for downstream models. Mapped intents and applied syntactic tagging while preserving semantic context and cultural nuances. Ensured consistency through careful validation and conflict resolution practices. • Performed text classification and intent mapping for NLP model training • Applied syntactic tagging and context-aligned labeling • Annotated text inputs with entity-oriented categories (NER-style classification) • Maintained quality control via validation against rigorous gold standards

2025 - Present

Data Annotation & AI Training Specialist (Freelance/Remote Technical Consultant) — computer vision annotation and quality control

CVATImageObject Detection

Provided high-precision computer vision annotations for multimodal machine learning training workflows. Labeled both 2D/3D bounding boxes and pixel-level ground truth to support detection and spatial/navigation models. Performed rigorous validation to ensure label quality at scale. • Annotated 2D/3D bounding boxes for spatial and navigation-focused training • Created semantic segmentation masks for pixel-level supervision • Audited batches against gold-standard validation criteria to maintain ~99.2% accuracy • Automated dataset syntax parsing, format conversion, and sanity testing to support faster labeling pipelines

2025 - Present

Technology Solutions Developer (Independent Projects) — data extraction pipeline for training set preparation

OtherTextData Collection

Built pipelines to assemble structured training sets intended for development testing and analytic workflows. Collected and extracted labeled-ready data using web scraping and API integrations. Focused on producing clean, consistent datasets suitable for direct downstream processing. • Assembled custom training datasets via web scraping and API integrations • Optimized data parsing logic for consistent formatting • Improved relational database schemas supporting dataset preparation • Ensured structured outputs for downstream analytical use

2024 - 2024

Work History