> Markdown version of [/jobs/ext/3835321-data-labeling-specialist](https://www.wearedevelopers.com/jobs/ext/3835321-data-labeling-specialist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Labeling Specialist

- **Company:** SHIPIN GA LLC
- **Location:** Seattle, WA, United States
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Artificial Intelligence, Data Analysis, Computer Vision, Spreadsheets, Data Cleansing, Monitoring of Systems, Python (Programming Language), Machine Learning, Data Processing, Model Validation, Information Technology
- **Published:** October 19, 2026
- **Apply:** https://www.thejobnetwork.com/job/39c50f6b-89ad-4368-8bf4-991d7ee606db/data-labeling-specialist

## About the Role

* Bachelor's degree in Computer Science, Information Technology, or a related field.
 * Hands-on experience in QA, data annotation, data moderation, system monitoring, or data analysis.
 * Strong analytical and problem-solving abilities.
 * Ability to work both independently and collaboratively in dynamic, fast-paced environments.
 * Strong communication and teamwork skills.

Nice to Have

 * Proficiency in Python for data manipulation and analysis.
 * Strong skills in Google Spreadsheets and Microsoft Excel.
 * Expertise in QA methodologies, data annotation, and system monitoring.

## Description

We are seeking a detail-oriented Data Labeling Specialist to join our team. In this role, you will play a key part in supporting our machine learning and AI initiatives by ensuring data quality, reviewing AI outputs, and documenting processes to drive continuous improvement., Data Labeling

 * Review and annotate datasets according to predefined guidelines (Segmentation masks, Bounding boxes, Classifications).
 * Accurately label and categorize data elements to support AI/ML initiatives.
 * Ensure consistency and quality across all annotation processes to maintain high-quality datasets.

Model Quality

 * Review and validate AI outputs to ensure accuracy.
 * Collaborate with Computer Vision researchers and Product Managers to improve AI model performance.

Documentation & Reporting

 * Document annotation processes, data cleaning procedures, and model validation workflows.
 * Generate regular reports on data quality, system performance, and analysis insights for leadership review.