Andrew Helmer

Key Skills

Software

AWS SageMaker

Appen

CloudFactory

CrowdSource

Data Annotation Tech

Dataloop

Deep Systems

Encord

Google Cloud Vertex AI

Labelbox

Label Studio

OneForma

Scale AI

Toloka

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Audio Recording

Classification

Computer Programming Coding

Data Collection

Diagnosis

Freelancer Overview

I’ve spent the past few years working closely on AI training projects, mainly focused on tasks like data labeling, prompt writing, and evaluating model responses. I’ve contributed to projects involving natural language processing, computer vision, and large language models, where my job was to make sure the data being used was accurate, clear, and useful for training. What sets me apart is my attention to detail and ability to follow complex guidelines while still thinking critically about quality and intent. I’m comfortable reviewing large sets of data, spotting inconsistencies, and suggesting improvements. I’ve used tools like Labelbox and internal annotation platforms, and I really enjoy the process of helping AI systems get better at understanding how people actually communicate.

Labeling Experience

Text Categorization

Scale AITextText SummarizationTranslation Localization

I contributed to an AI/NLP training project focused on improving text classification capabilities in large language models. Using Scale AI’s labeling platform, I categorized a wide range of user-generated content into predefined classes such as topic, intent, and sentiment. The project required careful reading and interpretation of short-form and long-form text, strict adherence to annotation guidelines, and flagging edge cases or ambiguous entries for review. I consistently ensured high-quality, accurate labels that helped refine model understanding of language patterns and contextual meaning across various content types.

I contributed to an AI/NLP training project focused on improving text classification capabilities in large language models. Using Scale AI’s labeling platform, I categorized a wide range of user-generated content into predefined classes such as topic, intent, and sentiment. The project required careful reading and interpretation of short-form and long-form text, strict adherence to annotation guidelines, and flagging edge cases or ambiguous entries for review. I consistently ensured high-quality, accurate labels that helped refine model understanding of language patterns and contextual meaning across various content types.

2023 - 2023

Image Annotation

LabelboxImageClassificationObject Detection

I worked on a computer vision dataset designed to help train autonomous vehicle systems. My tasks involved classifying road elements, detecting and labeling vehicles, pedestrians, and traffic signs, as well as annotating facial expressions for emotion recognition where applicable. Using Labelbox, I applied consistent labeling practices including bounding boxes and attribute tagging. I followed detailed guidelines and contributed to quality assurance by flagging edge cases and ambiguous images.

I worked on a computer vision dataset designed to help train autonomous vehicle systems. My tasks involved classifying road elements, detecting and labeling vehicles, pedestrians, and traffic signs, as well as annotating facial expressions for emotion recognition where applicable. Using Labelbox, I applied consistent labeling practices including bounding boxes and attribute tagging. I followed detailed guidelines and contributed to quality assurance by flagging edge cases and ambiguous images.

2022 - 2022

Education

Work History