We are looking for part-time Domain LLM Data Annotation Specialists to support high-quality data annotation and quality evaluation for large language model training and evaluation. This role covers specialized domains including finance, law, healthcare, insurance, semiconductors, manufacturing, energy, automotive, biopharma, e-commerce, and retail. Candidates should bring domain expertise or relevant professional experience to help ensure the accuracy, reliability, and practical value of expert-level data.
Responsibilities
- - Annotate, review, and evaluate domain-specific data for LLM training, evaluation, and post-training workflows.
- - Assess the factual accuracy, professional soundness, and completeness of model outputs in specialized domains.
- - Provide expert feedback on data quality, labeling guidelines, task design, and evaluation criteria.
- - Identify errors, inconsistencies, risks, and edge cases in domain-specific datasets.
- - Work with product, research, and data teams to improve annotation standards and quality control processes.
- - Support benchmarking and evaluation tasks for domain-specific LLM capabilities.
- - Complete annotation and review tasks on a part-time contractor basis with reliable delivery quality and timelines.
Requirements
- - Background or professional experience in one or more relevant domains, including finance, law, healthcare, insurance, semiconductors, manufacturing, energy, automotive, biopharma, e-commerce, or retail.
- - Strong domain knowledge and ability to judge the correctness, relevance, and quality of specialized content.
- - Careful attention to detail and strong sense of responsibility for data quality.
- - Ability to follow annotation guidelines and provide clear written feedback.
- - Good communication skills and ability to collaborate asynchronously with cross-functional teams.
- - Prior experience in data annotation, LLM evaluation, content review, research, consulting, or domain expert review is preferred.
- - Interest in AI, LLMs, and the application of AI systems in professional domains is a plus.
