Felix D.

Key Skills

Software

Data Annotation Tech

CVAT

Top Subject Matter

General AI/Data Labeling

Computer Vision

Speech/Language AI

Top Data Types

Image

Audio

Text

Top Task Types

Classification

Transcription

Computer Programming/Coding

Freelancer Overview

Data Annotator — SynapseMind. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Harvard University (2024). AI-training focus includes data types such as Image, Audio, and Text and labeling workflows including Classification and Transcription.

Labeling Experience

Data Annotator — SynapseMind

OtherImageClassification

As a Data Annotator at SynapseMind, I labeled image and text datasets to improve the accuracy of AI models. I evaluated images and text for context, quality, and relevance to ensure data consistency and adherence to annotation guidelines. My work contributed to refining AI-generated outputs and collaboration with quality assurance teams. • Labeled images and texts to enhance AI predictions • Ensured consistency through guideline-based annotations • Collaborated cross-functionally with QA teams • Supported model evaluation and optimization activities

2026 - 2026

ML Support: Text Dataset Annotation

OtherTextClassification

I prepared and annotated text datasets for supervised learning models in machine learning projects. Responsibilities included curating, reviewing, and labeling documents for clarity and relevance to training objectives. This supported reliable and accurate downstream AI tasks. • Curated text data for model input • Labeled documents according to task requirements • Conducted reviews to maintain data quality • Supported supervised learning initiatives in ML

Not specified

Transcription Project

OtherAudioTranscription

I produced accurate audio transcripts for AI training, supporting language model improvements and supervised learning. My responsibilities included converting spoken content to text with high fidelity and quality checking outputs. The work aided in building robust AI language models. • Transcribed audio to text for use in AI datasets • Quality-checked transcripts for accuracy • Facilitated training of language models • Enabled improved supervised learning from labeled data

Not specified

AI Image Annotation Project

OtherImageClassification

I validated AI image annotation datasets to support improved model predictions for various machine learning projects. Quality was ensured by cross-checking labels and refining boundary cases. These efforts supported enhancement and training of AI visual recognition models. • Conducted image dataset validation for model accuracy • Helped refine ambiguous cases to ensure high quality • Contributed to model training for visual recognition • Supported iterative dataset improvements for performance

Not specified

Education

Work History