Tommy Castol

Key Skills

Software

Appen

CVAT

Mercor

Telus

AWS SageMaker

Google Cloud Vertex AI

Labelbox

LabelImg

Label Studio

OneForma

Toloka

Other

Top Subject Matter

Natural Language Processing

AI Evaluation

Computer Science

Top Data Types

Image

Video

Text

Top Task Types

Bounding Box

Point/Key Point

Segmentation

Classification

Tracking

Polygon

Object Detection

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Text Generation

Fine-tuning

Computer Programming/Coding

Polyline

Question Answering

Text Summarization

Function Calling

Entity (NER) Classification

Freelancer Overview

AI Training Specialist / Data Annotation & Evaluation Analyst. Core strengths include Labelbox. AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Computer Programming.

Labeling Experience

Text Annotation and NLP Dataset Labeling for Large Language Models

TextClassification

Worked on AI training projects focused on large-scale text dataset annotation to support the development of natural language processing (NLP) and large language models (LLMs). Responsible for labeling and classifying text data for tasks such as Named Entity Recognition (NER), sentiment analysis, intent classification, and topic categorization. Performed prompt and response writing for supervised fine-tuning (SFT) datasets, evaluated AI-generated outputs, and rated model responses based on accuracy, relevance, safety, and coherence. Contributed to question-answering and text summarization datasets to improve model understanding and reasoning capabilities. Processed and reviewed thousands of text samples while following detailed annotation guidelines to ensure consistency and high-quality outputs. Maintained strict quality assurance standards through review cycles, error detection, and adherence to project requirements, helping improve overall dataset reliability and machine learning model performance.

Worked on AI training projects focused on large-scale text dataset annotation to support the development of natural language processing (NLP) and large language models (LLMs). Responsible for labeling and classifying text data for tasks such as Named Entity Recognition (NER), sentiment analysis, intent classification, and topic categorization. Performed prompt and response writing for supervised fine-tuning (SFT) datasets, evaluated AI-generated outputs, and rated model responses based on accuracy, relevance, safety, and coherence. Contributed to question-answering and text summarization datasets to improve model understanding and reasoning capabilities. Processed and reviewed thousands of text samples while following detailed annotation guidelines to ensure consistency and high-quality outputs. Maintained strict quality assurance standards through review cycles, error detection, and adherence to project requirements, helping improve overall dataset reliability and machine learning model performance.

2025 - Present

AI Training & Evaluation for Computer Science and Coding Tasks

TextComputer Programming Coding

Worked on AI training and evaluation projects focused on computer science and software engineering tasks. Responsible for creating and reviewing structured solutions to problems involving algorithms, data structures, and coding challenges. Evaluated multiple AI-generated and human-written solutions based on correctness, efficiency, readability, and adherence to best coding practices. Performed comparative analysis and ranking of responses to identify optimal solutions. Contributed to datasets involving question answering, text generation, and coding-related tasks used to train and improve large language models. Followed detailed evaluation guidelines and applied consistent scoring criteria to ensure high-quality outputs. Maintained structured datasets and ensured accuracy, consistency, and completeness across large volumes of evaluation tasks.

Worked on AI training and evaluation projects focused on computer science and software engineering tasks. Responsible for creating and reviewing structured solutions to problems involving algorithms, data structures, and coding challenges. Evaluated multiple AI-generated and human-written solutions based on correctness, efficiency, readability, and adherence to best coding practices. Performed comparative analysis and ranking of responses to identify optimal solutions. Contributed to datasets involving question answering, text generation, and coding-related tasks used to train and improve large language models. Followed detailed evaluation guidelines and applied consistent scoring criteria to ensure high-quality outputs. Maintained structured datasets and ensured accuracy, consistency, and completeness across large volumes of evaluation tasks.

2023 - Present

Computer Vision Data Labeling for Object Detection & Tracking

LabelboxImageBounding Box

Worked as an AI Training Specialist on multiple large-scale computer vision and audio annotation projects focused on improving machine learning model accuracy. Annotated thousands of images and video frames using bounding boxes, polygons, segmentation masks, and keypoints for object detection, tracking, and scene understanding tasks. Performed frame-by-frame video annotation to track moving objects across sequences and prepared datasets in YOLO, COCO, and Pascal VOC formats. Conducted audio transcription and classification tasks with strict accuracy requirements. Maintained high-quality standards by following detailed annotation guidelines, performing QA checks, and correcting inconsistencies. Collaborated with ML engineers to refine labeling strategies, reduce annotation errors, and optimize datasets for training and evaluation.

Worked as an AI Training Specialist on multiple large-scale computer vision and audio annotation projects focused on improving machine learning model accuracy. Annotated thousands of images and video frames using bounding boxes, polygons, segmentation masks, and keypoints for object detection, tracking, and scene understanding tasks. Performed frame-by-frame video annotation to track moving objects across sequences and prepared datasets in YOLO, COCO, and Pascal VOC formats. Conducted audio transcription and classification tasks with strict accuracy requirements. Maintained high-quality standards by following detailed annotation guidelines, performing QA checks, and correcting inconsistencies. Collaborated with ML engineers to refine labeling strategies, reduce annotation errors, and optimize datasets for training and evaluation.

2023 - Present

Large-Scale Image & Video Annotation for Computer Vision Models

VideoBounding Box

Worked on multiple AI training projects involving large-scale image, video, and audio datasets used for machine learning and computer vision model development. Responsible for annotating thousands of images and video frames using bounding boxes, polygons, segmentation masks, and keypoints to identify and track objects accurately. Performed frame-by-frame video annotation for object tracking and action recognition tasks while ensuring temporal consistency across frames. Conducted audio transcription and classification tasks to support speech recognition and NLP models. Prepared datasets in industry-standard formats such as YOLO, COCO, and Pascal VOC to ensure compatibility with machine learning pipelines. Maintained strict adherence to annotation guidelines and performed quality assurance checks to achieve high accuracy and consistency across datasets.

Worked on multiple AI training projects involving large-scale image, video, and audio datasets used for machine learning and computer vision model development. Responsible for annotating thousands of images and video frames using bounding boxes, polygons, segmentation masks, and keypoints to identify and track objects accurately. Performed frame-by-frame video annotation for object tracking and action recognition tasks while ensuring temporal consistency across frames. Conducted audio transcription and classification tasks to support speech recognition and NLP models. Prepared datasets in industry-standard formats such as YOLO, COCO, and Pascal VOC to ensure compatibility with machine learning pipelines. Maintained strict adherence to annotation guidelines and performed quality assurance checks to achieve high accuracy and consistency across datasets.

2024 - 2025

Education

Work History