Remote Data Annotation Specialist

About the Role

This full-time position offers remote data annotation and evaluation tasks supporting projects based in Berlin. You will be responsible for creating, reviewing, and ensuring the quality of training data used for advanced AI and machine learning applications, including natural language processing (NLP), computer vision, and content safety.

Primary Responsibilities

• Annotate and assess datasets encompassing text, images, audio, and video based on established project-specific guidelines.
• Conduct quality assurance checks such as spot verifications, error categorization, and corrections to guarantee training data integrity.
• Engage in reinforcement learning with human feedback (RLHF) style preference rankings, prompt assessments, and rubric-based evaluations of large language models (LLMs).
• Perform NLP-related assignments including classification, summarization scoring, and named entity recognition.
• Assist with computer vision labeling tasks involving bounding boxes, polygons, keypoints, and attribute tags.
• Implement content safety protocols by labeling and flagging sensitive or policy-relevant materials.
• Identify and document unusual cases, suggest improvements to guidelines, and help minimize annotation inconsistencies over time.
• Effectively utilize labeling tools, achieve designated throughput and quality benchmarks, and communicate any challenges in a remote work environment.

Qualifications and Experience

• Mid to senior-level experience in data annotation, labeling, quality assurance evaluation, or related AI data operational roles.
• Exceptional attention to detail with a strong ability to provide clear written justifications for ambiguous annotation scenarios.
• Preferably experienced with RLHF methodologies, prompt evaluation techniques, and workflows involving large language model training.
• Knowledgeable about compliance with annotation guidelines and maintaining high training data quality standards.

Additional Details

The position is fully remote despite the Berlin location reference, which is primarily a search or location tag. Candidates apply through the company platform to be matched with projects that fit their expertise and quality metrics.