Ndumba Brian Mwenda Ct10116

Key Skills

Software

Labelbox

Remotasks

Mercor

OneForma

Telus

CVAT

Data Annotation Tech

Mindrift

OpenCV AI Kit (OAK)

Label Studio

Lionbridge

Top Subject Matter

Artificial Intelligence

Machine Learning

Nlp Domain Expertise

Top Data Types

Video

Computer Code Programming

Image

Top Task Types

RLHF

Classification

Prompt Response Writing SFT

Computer Programming Coding

Evaluation Rating

Fine Tuning

Transcription

Question Answering

Text Generation

Text Summarization

Object Detection

Function Calling

Bounding Box

Polygon

Entity Ner Classification

Cuboid

Data Collection

Segmentation

Point Key Point

Red Teaming

Polyline

Freelancer Overview

Senior AI/Data Training Specialist. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, Remotasks, and Internal. Education includes Doctor of Philosophy, Harvard University and Bachelor of Science in Computer Science. AI-training focus includes data types such as Text and Image and labeling workflows including RLHF, Classification, and Evaluation.

Labeling Experience

Senior AI/Data Training Specialist

LabelboxTextRLHF

As a Senior AI/Data Training Specialist at Upwork, I led the development and evaluation of AI models using large annotated datasets. I established data labeling standards to enhance annotation consistency and conducted QA audits to ensure data quality. I worked closely with machine learning developers to improve models based on supervised and reinforcement learning feedback. • Managed annotated datasets involving text, image, and audio data • Developed and enforced criteria for consistent data labeling • Performed quality assurance audits to minimize model error • Conducted large language model (LLM) training tasks including bias detection, response ranking, and rapid evaluation.

As a Senior AI/Data Training Specialist at Upwork, I led the development and evaluation of AI models using large annotated datasets. I established data labeling standards to enhance annotation consistency and conducted QA audits to ensure data quality. I worked closely with machine learning developers to improve models based on supervised and reinforcement learning feedback. • Managed annotated datasets involving text, image, and audio data • Developed and enforced criteria for consistent data labeling • Performed quality assurance audits to minimize model error • Conducted large language model (LLM) training tasks including bias detection, response ranking, and rapid evaluation.

2023 - Present

Video Data Annotation Specialist

VideoBounding Box

Annotated approximately 20 hours of football match footage using CVAT for machine learning dataset preparation. The project involved labeling players using bounding boxes, tracking player movement across frames, and ensuring consistent identity assignment throughout sequences. Tasks included frame-by-frame video annotation, object tracking, and maintaining high accuracy in dynamic scenes with multiple overlapping subjects. I completed over 50,000 annotation items in 6 days which was a very tight deadline. Ensured quality by adhering to strict annotation guidelines, maintaining consistency in labeling across frames, and performing self-review checks to minimize errors. Delivered annotations within the required time while meeting performance and accuracy expectations for AI model training.

Annotated approximately 20 hours of football match footage using CVAT for machine learning dataset preparation. The project involved labeling players using bounding boxes, tracking player movement across frames, and ensuring consistent identity assignment throughout sequences. Tasks included frame-by-frame video annotation, object tracking, and maintaining high accuracy in dynamic scenes with multiple overlapping subjects. I completed over 50,000 annotation items in 6 days which was a very tight deadline. Ensured quality by adhering to strict annotation guidelines, maintaining consistency in labeling across frames, and performing self-review checks to minimize errors. Delivered annotations within the required time while meeting performance and accuracy expectations for AI model training.

2025 - 2026

AI Data Trainer / Machine Learning Analyst

RemotasksImageClassification

During my role as an AI Data Trainer / Machine Learning Analyst at Fiver, I managed and annotated datasets for computer vision and natural language processing applications. I completed labeling tasks focused on categorization, entity recognition, and sentiment analysis, supporting model testing and benchmarking. I applied data cleaning techniques and contributed to AI model validation to enhance overall data integrity. • Curated datasets for image classification and text entity recognition • Labeled data for sentiment analysis and categorization tasks • Evaluated and validated AI-generated results for accuracy • Used annotation tools such as Remotasks and Labelbox to enhance quality control.

During my role as an AI Data Trainer / Machine Learning Analyst at Fiver, I managed and annotated datasets for computer vision and natural language processing applications. I completed labeling tasks focused on categorization, entity recognition, and sentiment analysis, supporting model testing and benchmarking. I applied data cleaning techniques and contributed to AI model validation to enhance overall data integrity. • Curated datasets for image classification and text entity recognition • Labeled data for sentiment analysis and categorization tasks • Evaluated and validated AI-generated results for accuracy • Used annotation tools such as Remotasks and Labelbox to enhance quality control.

2021 - 2023

AI Research Assistant (PhD Program)

Text

As an AI Research Assistant in a PhD program, I created and annotated machine learning datasets to support research on data efficiency and model accuracy. I designed data pipelines for validation, annotation, and preprocessing to optimize AI training processes. My work included publishing studies on data annotation systems, supervising junior researchers, and leading validation projects. • Developed experimental datasets for AI training and evaluation • Built and managed pipelines for data annotation and preprocessing • Focused on improving model quality using validated data • Engaged in mentoring and collaborative research within AI and data science.

As an AI Research Assistant in a PhD program, I created and annotated machine learning datasets to support research on data efficiency and model accuracy. I designed data pipelines for validation, annotation, and preprocessing to optimize AI training processes. My work included publishing studies on data annotation systems, supervising junior researchers, and leading validation projects. • Developed experimental datasets for AI training and evaluation • Built and managed pipelines for data annotation and preprocessing • Focused on improving model quality using validated data • Engaged in mentoring and collaborative research within AI and data science.

2020 - 2023

Education

Work History