Remote Data Annotation Jobs Dublin

Rex.zone is hiring for remote data annotation jobs supporting AI training workflows, including data labeling, RLHF evaluation, prompt evaluation, and training data QA. In this full-time role, you will follow annotation guidelines, resolve edge cases, and deliver high-quality labeled datasets that improve large language model evaluation, NLP classification, named entity recognition, computer vision annotation, and content safety labeling. You will work with structured rubrics, calibration sessions, and quality audits to drive model performance improvement across real-world LLM training pipelines. Explore Rex.zone opportunities designed for mid-senior annotators who value accuracy, consistency, and measurable training data quality outcomes.

Job Heading: Remote Data Annotation Jobs Dublin

About the Role

You will label and evaluate multimodal training data to support LLM training pipelines and downstream model performance improvement. This includes RLHF preference ranking, prompt response evaluation, and task-based data labeling for NLP and computer vision, while maintaining strict annotation guidelines compliance and high training data quality.

Key Responsibilities

Deliver accurate labels and evaluations across text, image, and safety datasets; apply rubric-based QA evaluation and escalation for ambiguous edge cases; perform RLHF pairwise comparisons and preference judgments; complete named entity recognition and intent classification tasks; annotate computer vision data (bounding boxes, polygons, segmentation) as required; conduct content safety labeling for policy categories and risk severity; participate in calibration sessions to reduce inter-annotator variance; document decisions to improve annotation guidelines and audit readiness; meet throughput targets without sacrificing consistency and precision.

What You Will Work On

Large language model evaluation, prompt evaluation for helpfulness and factuality, RLHF ranking tasks, data labeling for NLP datasets, named entity recognition, computer vision annotation for detection and segmentation, and content safety labeling for trust and safety datasets. You will contribute to training data quality initiatives that directly influence model performance improvement.

Required Qualifications

Mid-senior experience in data annotation, QA evaluation, or AI data operations; strong written English and attention to detail; proven ability to follow rubrics and annotation guidelines compliance requirements; familiarity with NLP concepts (classification, NER) and/or computer vision annotation; ability to reason about ambiguous cases and produce consistent judgments; comfort working in remote tooling environments with feedback cycles and quality audits.

Preferred Qualifications

Hands-on experience with RLHF workflows, prompt evaluation, or LLM evaluation; exposure to content safety labeling and policy-driven annotation; experience with inter-annotator agreement processes, calibration, and adjudication; ability to write clear rationales that improve guideline clarity and reduce disagreement; familiarity with dataset versioning and basic QA sampling strategies.

Quality and Performance Expectations

You will be measured on training data quality, annotation guideline adherence, consistency, and audit outcomes. Success includes high agreement in calibration, low error rates in spot checks, and reliable delivery that supports model performance improvement in LLM training pipelines.

Who This Role Is For

Candidates seeking remote, full-time data annotation work aligned to Dublin job searches, including professionals from annotation vendors, AI labs, tech startups, BPOs, and trust-and-safety teams. This role is suitable for annotators comfortable with both informational tasks (understanding guidelines and tasks) and transactional goals (completing high-quality production labeling at scale).

How to Apply on Rex.zone

Apply through Rex.zone by submitting your profile and completing any required screening tasks. Ensure your experience highlights data labeling, RLHF, QA evaluation, and guideline compliance. If you have domain strengths in NLP, computer vision, or content safety labeling, include task examples and quality metrics where possible.

Frequently Asked Questions

Q: Are these remote data annotation jobs in Dublin actually remote?
Yes. The remote type is Remote, and the work is performed remotely using Rex.zone workflows and tools. The “Dublin” keyword aligns to search intent while the role remains explicitly Remote.
Q: Is this a full-time job or contract/freelance work?
This posting is FULL_TIME. Rex.zone may also list contract or freelance roles on the platform, but this specific role is full-time and remote.
Q: What types of tasks are included in data annotation for LLMs?
Common tasks include data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, named entity recognition, content safety labeling, and computer vision annotation, all designed to improve training data quality and model performance.
Q: What skills should I emphasize to match this role?
Emphasize data annotation, data labeling, RLHF, prompt evaluation, QA evaluation, LLM evaluation, named entity recognition, computer vision annotation, content safety labeling, and annotation guidelines compliance, with examples of training data quality impact.
Q: What experience level is expected?
The experience level is Mid-Senior. Candidates should be comfortable making consistent judgments, documenting rationales, and maintaining quality under production throughput targets.
Q: Which industries and employer types does this role support?
The role supports Technology workflows and may serve AI labs, tech startups, annotation vendors, and BPO-style operations, depending on the dataset and model training pipeline needs.

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