Mike Kyea

Key Skills

Software

AWS SageMaker

Anno-Mage

Appen

Argilla

Axiom AI

Clickworker

CloudFactory

CrowdFlower

CrowdSource

CVAT

Data Annotation Tech

Dataloop

Datatroniq

Datumbox

Datasaur

Datature

Dataturk

Deep Systems

Diffgram

Doccano

Encord

Figure Eight

Google Cloud Vertex AI

Hasty

HiveMind

Humanatic

iMerit

Img Lab

Kili Technology

Labelbox

LabelImg

Label Studio

LightTag

Lionbridge

Mighty AI

Mindrift

OneForma

OpenCV AI Kit (OAK)

Playment

Prodigy

Redbrick AI

Remotasks

Roboflow

Sama

Scale AI

Sloth

Snorkel AI

SuperAnnotate

Supervisely

Surge AI

Tagtog

Toloka

Telus

Trilldata Technologies

VoTT

V7 Labs

Other

Internal/Proprietary Tooling

Top Subject Matter

Autonomous Vehicles

Healthcare and Medical Imaging

Natural Language Processing (NLP)

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Action Recognition

Computer Programming Coding

Data Collection

Object Detection

Translation Localization

Freelancer Overview

With over six years of experience in data labeling and AI training data, I specialize in computer vision and natural language processing (NLP) projects. My expertise lies in creating high-quality annotations for image, video, and text datasets, ensuring precision and accuracy to enhance machine learning models' performance. I have a proven track record of leading annotation teams, optimizing workflows, and collaborating closely with AI research and development teams to drive innovative solutions. My key projects include annotating over 100,000 images for self-driving car applications, significantly improving object detection accuracy, and managing multilingual NLP model evaluations to enhance language understanding. I am proficient in using industry-leading tools such as Labelbox, CVAT, Prodigy, and AWS SageMaker Ground Truth. My attention to detail, problem-solving skills, and ability to manage large-scale datasets set me apart in the field, making me a valuable asset to any AI-driven project.

Labeling Experience

Code Snippet Classification for Automated Code Review

MindriftComputer Code ProgrammingComputer Programming Coding

Worked on a project to classify code snippets and functions for an automated code review system. Annotated various programming languages and frameworks, labeling code snippets based on functionality, complexity, and potential vulnerabilities. This data was used to train machine learning models to identify code patterns and suggest improvements or highlight potential issues in real-time.

Worked on a project to classify code snippets and functions for an automated code review system. Annotated various programming languages and frameworks, labeling code snippets based on functionality, complexity, and potential vulnerabilities. This data was used to train machine learning models to identify code patterns and suggest improvements or highlight potential issues in real-time.

2022 - 2023

Self-Driving Car Image Annotation

CVATImageBounding BoxObject Detection

Led a team to annotate over 100,000 images for a major self-driving car project. Utilized bounding boxes to label vehicles, pedestrians, traffic signs, and other relevant objects in urban and highway environments. The project significantly enhanced object detection accuracy by 25%, contributing to the development of safer and more reliable autonomous vehicles.

Led a team to annotate over 100,000 images for a major self-driving car project. Utilized bounding boxes to label vehicles, pedestrians, traffic signs, and other relevant objects in urban and highway environments. The project significantly enhanced object detection accuracy by 25%, contributing to the development of safer and more reliable autonomous vehicles.

2021 - 2022

Multilingual NLP Model Evaluation

ProdigyTextEntity Ner ClassificationText Summarization

Managed the evaluation of NLP models in English and Spanish for a conversational AI system. Annotated text data for named entity recognition, sentiment analysis, and text classification tasks. This project provided critical insights that improved language understanding and response accuracy by 15%, resulting in a more intuitive and effective user interaction.

Managed the evaluation of NLP models in English and Spanish for a conversational AI system. Annotated text data for named entity recognition, sentiment analysis, and text classification tasks. This project provided critical insights that improved language understanding and response accuracy by 15%, resulting in a more intuitive and effective user interaction.

2020 - 2021

Medical Image Annotation for Tumor Detection

SuperviselyImageSegmentation

Worked on a healthcare project to annotate medical images for tumor detection and segmentation. Performed pixel-wise annotation to identify and segment tumors in MRI and CT scans. The project supported the development of an AI model that improved early tumor detection rates by 20%, aiding in timely and accurate diagnosis.

Worked on a healthcare project to annotate medical images for tumor detection and segmentation. Performed pixel-wise annotation to identify and segment tumors in MRI and CT scans. The project supported the development of an AI model that improved early tumor detection rates by 20%, aiding in timely and accurate diagnosis.

2019 - 2020

Education

Work History