Gordan Muya

Key Skills

Software

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Entity Ner Classification

Segmentation

Relationship

Text Generation

Text Summarization

Freelancer Overview

I specialize in building intelligent automation and data engineering solutions, with hands-on experience in data labeling, annotation, and AI training data workflows. My background includes developing production-grade tools that streamline data pipelines, integrate multi-source datasets, and optimize annotation processes for engineering, healthcare, finance, and education domains. I have worked extensively with Python, cloud platforms (AWS), and modern AI/ML frameworks (OpenAI, Anthropic, TensorFlow, PyTorch), and have led projects involving geospatial data processing, simulation data generation, and NLP/LLM integrations for knowledge platforms. My expertise spans automated data cleaning, dataset curation, and workflow optimization to support high-quality AI model training, ensuring accuracy, scalability, and cross-domain adaptability. I am passionate about leveraging technology to deliver robust, ethical, and impactful AI solutions.

Labeling Experience

Data Annotator

MercorImageEntity Ner ClassificationSegmentation

Mercor’s Project Nova was a large scale AI training initiative that engaged thousands of contractors in carefully structured tasks to help improve machine learning models. Contributors were responsible for labeling and categorizing images, videos, and text, as well as evaluating AI-generated outputs to determine accuracy, relevance, and quality. The project aimed to provide more consistent work after the previous Musen project, though pay was slightly lower, offering contractors steady hours and a reliable workflow. Quality was taken seriously, with time-tracked work, reviewer feedback, and corrective loops ensuring that each contribution met the project’s standards. For the workers, Nova combined the routine of structured tasks with the tangible satisfaction of seeing their efforts directly improve AI systems, making it both challenging and meaningful work.

Mercor’s Project Nova was a large scale AI training initiative that engaged thousands of contractors in carefully structured tasks to help improve machine learning models. Contributors were responsible for labeling and categorizing images, videos, and text, as well as evaluating AI-generated outputs to determine accuracy, relevance, and quality. The project aimed to provide more consistent work after the previous Musen project, though pay was slightly lower, offering contractors steady hours and a reliable workflow. Quality was taken seriously, with time-tracked work, reviewer feedback, and corrective loops ensuring that each contribution met the project’s standards. For the workers, Nova combined the routine of structured tasks with the tangible satisfaction of seeing their efforts directly improve AI systems, making it both challenging and meaningful work.

2025

Education

Work History