Today Searchspring is proud to be the industry leader in providing enhanced solutions on native ecommerce platforms for on-site search, merchandising, personalization, insights, and more. We help retailers drive the best shopper experience possible which leads to better conversion rates and increased customer loyalty. With offices and remote employees all over the world, every Searchspring employee is on a mission to provide the ultimate shopper experience.

Job Description :

We are seeking a detail-oriented Data Labeler to help build and validate high-quality datasets for AI model development. You will work with text, numerical, and image data, ensuring accuracy, consistency, and schema compliance. Alongside dataset creation, you will verify model predictions to ensure outputs meet internal quality standards and SLAs, directly supporting reliable datasets and strong model performance.

Responsibilities :

- Assist in building and curating high-quality datasets for AI model training and evaluation.

- Perform labeling, tagging, categorization, and annotation tasks across text, numerical, and image data.

- Verify data integrity and compliance against schemas, guidelines, or external data sources.

- Review and validate AI model predictions to ensure they meet internal SLAs for accuracy, consistency, and reliability.

- Flag and document errors or misclassifications for retraining or process improvement.

- Ensure accuracy and consistency across large volumes of data, flagging anomalies or issues.

- Collaborate with stakeholders to refine guidelines and processes.

- Maintain organized and well-documented labeling workflows, ensuring reproducibility and auditability.

- Provide feedback to improve labeling tools, processes, and quality assurance checks.

Skills and Qualifications :

Requirements :

- Strong proficiency in Excel or Google Sheets (formulas, pivot tables, lookups, filters, and data cleaning functions).

- Excellent written English, with high attention to grammar, spelling, and clarity.

- Strong attention to detail and ability to follow labeling instructions precisely.

- Ability to work efficiently with large datasets and repetitive tasks without loss of accuracy.

- Basic understanding of data structures, schemas, and quality control processes.

Desirable :

- Understanding of how labeled data and prediction QA feed into model retraining and improvement.

- Prior experience in dataset curation or quality assurance against SLAs.

- Knowledge of Python or SQL for data manipulation.