Remote AI data labeling jobs at Rex.zone connect skilled annotators with AI labs, tech startups, BPOs, and annotation vendors. This role is a search-recognizable entity: data labeling specialist supporting RLHF, prompt evaluation, QA evaluation, named entity recognition (NER), computer vision annotation, content safety labeling, and LLM training pipelines. You’ll improve training data quality through annotation guidelines compliance and rigorous large language model evaluation to drive model performance improvement. Workflows span NLP, CV, multimodal datasets, chat safety, and benchmarking. Roles include remote, contract, freelance, full-time, entry-level, and senior tracks, with clear tooling, SOPs, and quality metrics. Apply on Rex.zone to join vetted projects that power production AI systems.
As a remote data labeling specialist, you will craft high-quality annotations for NLP, computer vision, and multimodal datasets used in LLM training pipelines and evaluation. Projects span RLHF preference labeling, prompt evaluation, named entity recognition, taxonomy mapping, content safety moderation, and structured QA checks to ensure training data quality.
RLHF pairwise preference labeling; chat and prompt evaluation; named entity recognition (NER) for text; computer vision annotation (bounding boxes, polygons, segmentation); content safety labeling; multilingual classification; ontology design; benchmarking and large language model evaluation; guideline updates and versioning.
Follow annotation guidelines compliance across tasks; maintain training data quality via audits and spot checks; execute model performance improvement feedback cycles; run large language model evaluation with standardized rubrics; document edge cases; escalate ambiguities; collaborate with QA leads; meet throughput targets while preserving accuracy.
Attention to detail; ability to interpret complex labeling instructions; familiarity with NLP and computer vision basics; experience with JSON/CSV formats; comfort with annotation tools; understanding of taxonomy/ontology; strong written communication; ethics and privacy awareness; plus for Python/SQL, evaluation frameworks, and prompt engineering.
Remote roles include contract, freelance, and full-time options across entry-level and senior tracks. Opportunities span NLP, computer vision, content safety, and LLM training. Employers include AI labs, tech startups, BPOs, and annotation vendors. Location-flexible with region-specific compliance and scheduling windows.
Use Rex.zone workspaces with browser-based labeling tools, custom ontologies, rubric-driven QA evaluation, and LLM eval harnesses. Projects may integrate SDKs, APIs, or batch pipelines. SOPs, exemplars, and checklists are provided to improve consistency and reduce guideline drift.
Rates vary by domain, complexity, and throughput: USD $15–$35 per hour, or task-based pricing for microbatches. Senior QA/evaluator roles may earn higher rates. Performance bonuses and milestone incentives may apply on select projects.
Create a Rex.zone profile, complete the skills checklist, and pass short calibration tasks for your chosen domain (NLP, CV, content safety, RLHF). Qualified candidates receive invites to active projects with clear scope, timelines, and pay structures.
It’s structured annotation and evaluation work that feeds LLM training pipelines, including RLHF preference labeling, prompt and chat evaluation, NER, computer vision tasks, and content safety classification.
NLP (classification, NER, summarization), computer vision (detection, segmentation), multimodal tasks, content safety labeling, and large language model evaluation for benchmarking.
Entry-level roles are available; senior roles require proven quality metrics, guideline mastery, and prior QA/evaluation work. Calibration tasks help align your skill level with suitable projects.
Hourly and per-task models are used depending on the project. Rates reflect complexity, accuracy requirements, and volume commitments, with potential bonuses for consistent high-quality output.
Rex.zone provides web-based annotation tools, rubrics, and QA workflows. Some projects may involve JSON-based submissions, spreadsheets, or integrations with LLM evaluation harnesses.
You’ll follow annotation guidelines compliance, complete spot checks, and review feedback loops. QA leads provide audits and exemplars to maintain training data quality and model performance improvement.
Yes. Most projects are location-flexible with time zone windows for team syncs. Contract, freelance, and full-time roles are available across regions subject to compliance.
AI labs, tech startups, BPOs, and specialized annotation vendors use Rex.zone to source vetted annotators and evaluators for production-grade AI workflows.
Apply through Rex.zone, complete your profile, choose domains of interest, and finish calibration tasks. Once qualified, you can join active remote projects aligned with your skills and schedule.
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