[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-remote-data-annotation-jobs-barcelona":3},{"Ques":4,"Slug":28,"Header":29,"job_category":57},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19,22,25],{"A":8,"Q":9},"The role is Remote and listed under Country: US for job metadata. The work supports Barcelona-oriented search intent and may involve Barcelona locale data, but the position itself is remote and not limited to on-site work.","Are these remote data annotation jobs Barcelona-based or US-based?",{"A":11,"Q":12},"Typical workflows include NLP labeling (classification, named entity recognition), prompt evaluation, RLHF preference ranking, QA evaluation on labeled datasets, and occasional computer vision annotation and content safety labeling depending on project needs.","What kind of data labeling will I do?",{"A":14,"Q":15},"You will compare multiple model responses, rank outputs by rubric, provide concise rationales, flag policy violations, and help generate preference data that improves model alignment and overall model performance improvement.","What does RLHF work look like in practice?",{"A":17,"Q":18},"Yes. Employment Type is FULL_TIME and Remote Type is Remote. You will work in an asynchronous, tool-based workflow managed through Rex.zone.","Is this role full-time and fully remote?",{"A":20,"Q":21},"Quality is measured through annotation guidelines compliance, audits, gold tasks, inter-annotator agreement, and QA evaluation reviews focused on training data quality and consistency.","How is quality measured?",{"A":23,"Q":24},"Projects can cover NLP, large language model evaluation, computer vision annotation, and content safety labeling for AI labs, tech startups, BPOs, and annotation vendors.","What domains might I support?",{"A":26,"Q":27},"Tool familiarity is helpful, but the most important skills are careful rubric adherence, consistent decision-making, and clear written rationales. Rex.zone projects provide onboarding and calibration materials.","Do I need prior experience with annotation tools?","remote-data-annotation-jobs-barcelona",{"desc":30,"title":31,"content":32},"Remote data annotation jobs Barcelona at Rex.zone focus on creating and evaluating training data for AI\u002FML systems, including data labeling, RLHF, prompt evaluation, and QA evaluation for large language model training pipelines. You will follow annotation guidelines compliance to deliver training data quality that supports model performance improvement across NLP, computer vision annotation, named entity recognition, and content safety labeling. This full-time remote role supports AI labs, tech startups, and annotation vendors with consistent, audit-ready datasets and evaluation signals.","Remote Data Annotation Jobs Barcelona",[33,36,39,42,45,48,51,54],{"h2":34,"desc":35},"LinkedIn Job Metadata — Remote Data Annotation Jobs Barcelona","Title: Remote Data Annotation Specialist (Barcelona)\nDate: 25-02-2026\nCompany: Rex.zone\nCountry: US\nRemote Type: Remote\nEmployment Type: FULL_TIME\nExperience Level: Mid-Senior\nIndustry: Technology\nJob Function: Engineering\nSkills: Remote data annotation, data labeling, RLHF, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, content safety labeling, annotation guidelines compliance, training data quality\nSalary Currency: USD\nSalary Min: 63360\nSalary Max: 126720\nPay Period: YEAR",{"h2":37,"desc":38},"About the Role","As a Remote Data Annotation Specialist (Barcelona) on Rex.zone, you will label and evaluate multi-modal AI training data to improve large language model evaluation and downstream model behavior. Your work spans text classification, NER, summarization checks, preference ranking for RLHF, and prompt-response grading, as well as computer vision annotation when needed. You will apply detailed rubrics, maintain annotation guidelines compliance, and help teams measure training data quality, reduce noise, and support model performance improvement.",{"h2":40,"desc":41},"What You Will Do","You will execute data labeling tasks for NLP and LLM training pipelines, including intent tagging, sentiment, topic, and named entity recognition; perform RLHF-style preference ranking and pairwise comparisons for prompt evaluation; run QA evaluation on labeled datasets, resolve conflicts, and document edge cases; annotate computer vision data when required (bounding boxes, polygons, keypoints, image classification); conduct content safety labeling (toxicity, self-harm, hate, sexual content) with policy adherence; track production metrics (throughput, accuracy, inter-annotator agreement) and contribute to calibration sessions; collaborate asynchronously with project leads and follow secure data handling procedures.",{"h2":43,"desc":44},"Required Skills and Experience","Mid-Senior experience in data annotation, data labeling, QA evaluation, or search relevance evaluation; demonstrated ability to follow complex rubrics and maintain annotation guidelines compliance; strong written English for rationale-based grading and prompt evaluation; familiarity with NLP concepts (entities, intent, classification) and LLM evaluation; comfort working with web-based annotation tools and spreadsheet-like workflows; ability to identify ambiguous cases, propose guideline clarifications, and improve training data quality.",{"h2":46,"desc":47},"Nice to Have","Experience with RLHF workflows (preference data, ranking, critiques) and large language model evaluation; background in computer vision annotation (CV) including segmentation and keypoints; experience in content safety labeling or policy enforcement; exposure to QA processes such as gold sets, audits, and inter-annotator agreement; familiarity with multilingual data or locale-specific evaluation relevant to Barcelona-based user intent.",{"h2":49,"desc":50},"Work Model and Schedule","This is a FULL_TIME Remote role with asynchronous collaboration. You may support projects that serve global teams, including AI labs, tech startups, BPOs, and annotation vendors. Rex.zone provides task access, guidelines, and QA workflows; you contribute consistent labeling output and evaluation notes to improve training data quality.",{"h2":52,"desc":53},"How to Apply on Rex.zone","Apply through Rex.zone by completing your profile, confirming your availability for full-time remote work, and taking any required qualification tasks (example labeling, prompt evaluation, or QA checks). Selected candidates will receive project-specific annotation guidelines, calibration instructions, and quality targets.",{"h2":55,"desc":56},"Compensation","Salary is listed in USD with an annual pay period. Final compensation within the posted range depends on project complexity, QA responsibilities, and demonstrated accuracy during calibration.","AI Data Operations"]