Michael Addo

Key Skills

Software

CVAT

Labelbox

Label Studio

Other

Top Subject Matter

NLP/Obligation Extraction

NLP/Data Annotation

AI Data Validation

Top Data Types

Computer Code Programming

Geospatial Tiled Imagery

Image

Video

Text

Document

Top Label Types

Bounding Box

Polygon

Point Key Point

Segmentation

Classification

Fine Tuning

Entity Ner Classification

Data Collection

Freelancer Overview

Software/AI Engineer, 4th-ir. Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Other. AI-training focus includes data types such as Text and labeling workflows including Fine-tuning, Entity (NER) Classification, and Evaluation.

Labeling Experience

Software/AI Engineer, 4th-ir

TextFine Tuning

Built and trained an NLP model for an Obligation Extraction Tool to automatically identify and extract obligations from documents, focusing on fine-tuning with annotated textual data. Enhanced data processing pipelines to support accurate extraction by preparing and validating labeled datasets. Collaborated with cross-functional teams to ensure high annotation quality and robust model training. • Developed custom annotation schemas tailored for obligation extraction tasks. • Conducted manual and automated data labeling for text extraction. • Validated labels to maintain consistency and accuracy throughout the dataset. • Supported downstream deployment by refining label formats and structures.

Built and trained an NLP model for an Obligation Extraction Tool to automatically identify and extract obligations from documents, focusing on fine-tuning with annotated textual data. Enhanced data processing pipelines to support accurate extraction by preparing and validating labeled datasets. Collaborated with cross-functional teams to ensure high annotation quality and robust model training. • Developed custom annotation schemas tailored for obligation extraction tasks. • Conducted manual and automated data labeling for text extraction. • Validated labels to maintain consistency and accuracy throughout the dataset. • Supported downstream deployment by refining label formats and structures.

2024 - 2026

AI Data Validation Engineer, Turing

OtherText

Validated and audited large AI training datasets to ensure high standards of annotation integrity, accuracy, and consistency for agentic AI workflows. Used automated and manual tools for data validation and created JSON task structures for seamless function-calling by models. Documented quality standards and collaborated with AI researchers to align annotations with evolving model requirements. • Conducted data quality and consistency audits on AI training datasets. • Created structured tasks and refined label schemas for function-calling workflows. • Automated validation checks through custom Python scripts and SQL queries. • Aligned annotation approaches with best practices tailored for LLM and agent-based tasks.

Validated and audited large AI training datasets to ensure high standards of annotation integrity, accuracy, and consistency for agentic AI workflows. Used automated and manual tools for data validation and created JSON task structures for seamless function-calling by models. Documented quality standards and collaborated with AI researchers to align annotations with evolving model requirements. • Conducted data quality and consistency audits on AI training datasets. • Created structured tasks and refined label schemas for function-calling workflows. • Automated validation checks through custom Python scripts and SQL queries. • Aligned annotation approaches with best practices tailored for LLM and agent-based tasks.

2025 - 2025

AI Trainer, Invisible Technologies

OtherTextEntity Ner Classification

Collaborated with a distributed team to annotate and label large text, image, and document datasets, advancing NLP model accuracy through comprehensive entity recognition and tagging. Maintained high annotation quality by following strict guidelines and performing consistency checks on all submissions. Supported workflows across data labeling, annotation, and detailed sentiment and entity analysis for AI training tasks. • Performed text tagging and entity recognition using standardized NER frameworks. • Maintained batch-to-batch annotation quality through iterative corrections and feedback. • Labeled sentiment and mapped instructions into structured, actionable categories. • Supported annotation relevant to LLM instruction and robotics-style task understanding.

Collaborated with a distributed team to annotate and label large text, image, and document datasets, advancing NLP model accuracy through comprehensive entity recognition and tagging. Maintained high annotation quality by following strict guidelines and performing consistency checks on all submissions. Supported workflows across data labeling, annotation, and detailed sentiment and entity analysis for AI training tasks. • Performed text tagging and entity recognition using standardized NER frameworks. • Maintained batch-to-batch annotation quality through iterative corrections and feedback. • Labeled sentiment and mapped instructions into structured, actionable categories. • Supported annotation relevant to LLM instruction and robotics-style task understanding.

2025 - 2025

Data Annotator

CVATVideoBounding BoxPolygon

This project focuses on creating a high-quality annotated dataset to train and improve a large language model used in a warehouse robot assistant. The robot is expected to understand human instructions, identify objects in its environment, and perform simple warehouse tasks such as picking, sorting, moving, and placing items.

This project focuses on creating a high-quality annotated dataset to train and improve a large language model used in a warehouse robot assistant. The robot is expected to understand human instructions, identify objects in its environment, and perform simple warehouse tasks such as picking, sorting, moving, and placing items.

2024 - 2025

Data Annotation & Web Automation Analyst, Higher Data

OtherTextData Collection

Delivered annotated datasets for ML use cases, working with text, image, and video data, and supported AI data preparation workflows. Used browser automation and LLM tools for data extraction and schema mapping, transforming semi-structured inputs into structured, analysis-ready outputs. Improved annotation processes by automating validation, transformation, and export of datasets. • Created, cleaned, and validated annotations for text, image, and video data. • Applied automation and scripting to streamline data extraction and preparation for ML. • Utilized LLM-based tools for extracting and structuring annotated features. • Facilitated schema mapping and export into training-ready datasets.

Delivered annotated datasets for ML use cases, working with text, image, and video data, and supported AI data preparation workflows. Used browser automation and LLM tools for data extraction and schema mapping, transforming semi-structured inputs into structured, analysis-ready outputs. Improved annotation processes by automating validation, transformation, and export of datasets. • Created, cleaned, and validated annotations for text, image, and video data. • Applied automation and scripting to streamline data extraction and preparation for ML. • Utilized LLM-based tools for extracting and structuring annotated features. • Facilitated schema mapping and export into training-ready datasets.

2022 - 2022

Education

Work History