Data Annotation Specialist

Job Description

About Paladin Tech

At Paladin Tech, we build AI-powered products that transform complex data into actionable insights. Our portfolio includes solutions for deepfake detection, video and image analytics, big data intelligence, AI assistants, and real-time decision support systems. We help organizations enhance security, verify authenticity, optimize operations, and drive measurable results through cutting-edge AI, ML, and Big Data Analytics.

Summary

We are looking for a detail-oriented Data Annotation Specialist to support our machine learning initiatives. In this role, you will review, label, and annotate datasets (text, images, audio, or video), ensuring accuracy and consistency. You’ll work closely with the AI / ML engineering team to improve the quality of training data and contribute directly to building smarter, more reliable models.

Requirements

• Perform data labeling and annotation tasks with high accuracy and attention to detail.
• Follow defined annotation guidelines and continuously provide feedback to improve them.
• Identify inconsistencies, errors, and edge cases in datasets and escalate issues when needed.
• Ensure timely delivery of annotation tasks while maintaining high quality.
• Collaborate with engineers and researchers to understand annotation requirements and update workflows accordingly.
• Contribute to maintaining annotation tools and suggesting process improvements.
• Conduct quality checks on completed annotations to ensure consistency across the dataset.

Minimum Qualifications

Preferred Qualifications

Benefits

Requirements

Requirements : Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field. 4+ years of experience working with Neo4j or other graph databases. Strong proficiency in Cypher query language. Hands-on experience with graph data modelling and database optimization techniques. Proficiency in a backend programming language such as Java, Python, or Node.js. Experience with integrating graph databases into production applications. Familiarity with graph algorithms and analytics techniques. Knowledge of ETL pipelines, data integration tools, and API development. Understanding of database security, indexing, and scalability best practices. Excellent problem-solving skills and attention to detail. Preferred Skills : Experience with GraphQL and Neo4j GraphQL libraries. Familiarity with big data and cloud platforms (AWS, GCP, Azure). Knowledge of other NoSQL databases such as MongoDB or Cassandra.