[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-remote-data-annotator-jobs-warsaw":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},"Yes. Remote Type remains Remote, and day-to-day work is completed online with distributed teams through Rex.zone.","Are these remote data annotator jobs in Warsaw fully remote?",{"A":11,"Q":12},"Typical work includes data labeling, QA evaluation, RLHF evaluation (preference ranking), prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling depending on the project.","What kind of annotation work is included?",{"A":14,"Q":15},"Mid-Senior candidates should be comfortable with rubric-based judgments, preference comparisons, and identifying quality issues that affect model performance improvement in LLM training pipelines.","Do I need experience with large language model evaluation?",{"A":17,"Q":18},"This listing is FULL_TIME. Rex.zone may also host contract or freelance roles, but this posting’s Employment Type is FULL_TIME as specified.","Is this contract or freelance work?",{"A":20,"Q":21},"QA evaluation involves auditing labeled data for accuracy, consistency, and annotation guidelines compliance, measuring training data quality, and resolving edge cases to reduce noise in downstream model training.","What does QA evaluation mean in data annotation?",{"A":23,"Q":24},"Projects commonly span NLP, computer vision annotation, and content safety labeling, including named entity recognition, classification, segmentation, and large language model evaluation tasks.","What domains can projects cover?",{"A":26,"Q":27},"Skills aligned with remote data annotator work include data annotation, data labeling, RLHF evaluation, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, content safety labeling, annotation guidelines compliance, training data quality, and large language model evaluation.","What skills should match this keyword intent?","remote-data-annotator-jobs-warsaw",{"desc":30,"title":31,"content":32},"Remote data annotator jobs in Warsaw on Rex.zone focus on training-data creation for AI\u002FML systems, including data labeling, RLHF evaluation, prompt evaluation, and QA evaluation for large language model training pipelines. You will apply annotation guidelines compliance to produce training data quality that supports model performance improvement across NLP, computer vision annotation, named entity recognition, and content safety labeling. These full-time remote roles support AI labs, tech startups, BPOs, and annotation vendors building reliable LLM and multimodal models while maintaining accuracy, consistency, and privacy-aware handling of sensitive content.","Remote Data Annotator Jobs in Warsaw",[33,36,39,42,45,48,51,54],{"h2":34,"desc":35},"Job Heading: Remote Data Annotator Jobs in Warsaw","Date: 25-02-2026 | Company: Rex.zone | Country: US | Remote Type: Remote | Employment Type: FULL_TIME | Experience Level: Mid-Senior | Industry: Technology | Job Function: Engineering | Skills: Data annotation, data labeling, RLHF evaluation, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, content safety labeling, annotation guidelines compliance, training data quality, large language model evaluation | Salary Currency: USD | Salary Min: 63360 | Salary Max: 126720 | Pay Period: YEAR",{"h2":37,"desc":38},"About the Role","In this full-time remote role, you will create and evaluate training datasets used to improve large language models and multimodal AI systems. Your work includes data labeling, RLHF (Reinforcement Learning from Human Feedback) preference ranking, prompt evaluation, and QA evaluation to ensure training data quality and annotation guidelines compliance. You will collaborate with cross-functional teams to reduce ambiguity, surface edge cases, and support model performance improvement across NLP, computer vision annotation, named entity recognition, and content safety labeling workflows.",{"h2":40,"desc":41},"What You Will Do","You will annotate and review text, images, and conversational data according to detailed guidelines; perform RLHF preference judgments and comparative evaluations to support reinforcement learning workflows; execute prompt evaluation and large language model evaluation tasks to identify failure modes and hallucination patterns; run QA evaluation checks for consistency, inter-annotator agreement, and training data quality; label entities and relationships for named entity recognition and information extraction; support computer vision annotation tasks such as bounding boxes, polygons, keypoints, and segmentation masks; label content safety categories including harmful content, policy violations, and sensitive attributes; document edge cases, propose guideline clarifications, and communicate issues to project leads; follow secure data handling practices for privacy, confidentiality, and restricted content.",{"h2":43,"desc":44},"Required Qualifications","Mid-Senior experience in data annotation, data labeling, QA evaluation, or AI data operations; strong ability to follow annotation guidelines compliance and apply consistent decision-making; familiarity with large language model evaluation concepts such as preference ranking, rubric-based grading, and prompt evaluation; experience with NLP labeling tasks (classification, sentiment, NER) and\u002For computer vision annotation (bbox, segmentation) is preferred; ability to work independently in a remote environment with reliable internet and structured time management; comfort working with content safety labeling and potentially sensitive material; clear written communication for documenting rationales, edge cases, and feedback.",{"h2":46,"desc":47},"Tools and Workflows You May Use","Annotation platforms and labeling tools; QA evaluation checklists and sampling plans; taxonomy and rubric design for RLHF evaluation and prompt evaluation; issue tracking and workflow management; secure data access controls and audit-friendly documentation.",{"h2":49,"desc":50},"Who This Role Supports","These remote data annotator jobs support AI labs, tech startups, BPOs, and annotation vendors building NLP, computer vision, and content safety systems. Projects commonly include LLM training pipelines, large language model evaluation, RLHF datasets, named entity recognition corpora, and safety policy labeling.",{"h2":52,"desc":53},"Compensation","Salary range is 63360 to 126720 USD per year (FULL_TIME), depending on project scope, evaluation complexity, and QA responsibilities.",{"h2":55,"desc":56},"How to Apply on Rex.zone","Apply through Rex.zone by selecting the Remote Data Annotator Jobs in Warsaw listing, completing your profile, and submitting any required assessments related to data labeling, RLHF evaluation, prompt evaluation, or QA evaluation. Qualified applicants may be invited to a guideline calibration task and quality review.","AI Data Operations"]