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Remote Data Annotation Denver

Remote / Online - Candidates ideally in
Denver, Denver County, Colorado, 80230, USA
Listing for: Rex.zone
Full Time, Remote/Work from Home position
Listed on 2026-10-26
Job specializations:
  • IT/Tech
    Data Annotation/ AI Labeling, AI Evaluation
Salary/Wage Range or Industry Benchmark: 42000 - 54000 USD Yearly USD 42000.00 54000.00 YEAR
Job Description & How to Apply Below
Position: Remote Data Annotation Jobs in Denver

Remote Data Annotation Jobs in Denver (US-Remote) Join Rex.zone to deliver high-accuracy labeled datasets and evaluation judgments used to build and improve AI systems and large language model (LLM) training pipelines. Work includes data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, and content safety labeling while following strict annotation guidelines compliance.

Key Responsibilities
  • Perform data labeling for NLP tasks such as named entity recognition, sentiment, intent, and taxonomy-based classification
  • Complete RLHF-style ranking and preference labeling to support LLM evaluation and alignment
  • Run prompt evaluation and response grading for accuracy, helpfulness, policy compliance, and reasoning quality
  • Execute content safety labeling using client rubrics (hate/harassment, self-harm, sexual content, violence)
  • Annotate computer vision data when needed (bounding boxes, polygons, keypoints, segmentation masks)
  • Apply annotation guidelines compliance, flag ambiguous items, and document edge cases
  • Conduct QA evaluation (self-check and peer review), track error types, and drive quality improvements
  • Maintain secure handling of sensitive data and adhere to confidentiality and platform policies
Required Qualifications
  • Mid-Senior experience in data annotation, data labeling, QA review, or AI/ML evaluation workflows
  • Strong written communication for rationales and guideline interpretations
  • Ability to follow detailed rubrics with high consistency and quality standards
  • Comfort working with web-based annotation tools and task tracking
  • Understanding of LLM training concepts (supervised fine-tuning data, RLHF, evaluation sets)
Work Location and Schedule

Remote Type:
Remote (Denver-based candidates welcomed; work performed remotely within the US).

Employment Type:

Full-time with sustained throughput and quality expectations.

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