Mark Kamanda

Key Skills

Software

AWS SageMaker

Appen

CloudFactory

CVAT

Hasty

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Bounding Box

Classification

Cuboid

Polygon

Segmentation

Freelancer Overview

I am an experienced AI Training Data Specialist with over 3 years of expertise in data labeling and annotation across diverse domains, including Natural Language Processing (NLP), Computer Vision, and Generative AI. My background includes high-quality labeling for chatbots, sentiment analysis, and text classification, as well as image and video annotation for self-driving cars, road classification, and segmentation. I have also contributed to LLM evaluation, ensuring accurate and reliable outputs for real-world applications. What sets me apart is my versatility and attention to detail across industries such as autonomous driving, healthcare, customer support, and digital marketing. I excel in delivering structured, accurate datasets that power advanced AI and machine learning models. With proven experience at organizations like Cloudfactory and Pareto.ai, I bring both technical expertise and communication skills, enabling me to contribute effectively to projects that demand precision, scalability, and impact.

Labeling Experience

Autonomous Driving – Road Classification & Segmentation

CVATVideoBounding BoxPolygon

Contributed to the development of perception systems for self-driving cars by annotating large-scale image and video datasets. Tasks included road classification, lane marking, object detection (vehicles, pedestrians, traffic signs), and segmentation of road features to enhance model training for safe navigation. Maintained strict quality standards with multi-level QA checks to ensure accuracy and consistency across thousands of frames.

Contributed to the development of perception systems for self-driving cars by annotating large-scale image and video datasets. Tasks included road classification, lane marking, object detection (vehicles, pedestrians, traffic signs), and segmentation of road features to enhance model training for safe navigation. Maintained strict quality standards with multi-level QA checks to ensure accuracy and consistency across thousands of frames.

2022 - 2023

Education

Work History