Remote Data Annotator Jobs in Los Angeles

Rex.zone; Los Angeles (CA); Remote; USD 45,000 - 60,000; Full time

Job summary

Rex.zone is seeking mid-senior remote data annotators in a fully remote capacity to create and evaluate training data for AI/ML systems, including NLP, computer vision, and content safety workflows. You will follow detailed guidelines, complete calibrations, and contribute to high-quality datasets used in LLM training pipelines.

Responsibilities include applying labeling rules, performing RLHF tasks, and conducting QA evaluations while maintaining data quality under throughput targets.

Qualifications

• Experience in data annotation or QA evaluation.
• Familiarity with LLM evaluation concepts and rubrics.
• Ability to maintain data quality under throughput targets.

Responsibilities

• Apply data labeling rules to text, image, audio, or multimodal samples.
• Perform RLHF tasks (preference ranking, pairwise comparisons, rubric-based scoring)
• Conduct QA evaluation through self-checks, peer review, and targeted audits
• Complete NLP labeling such as named entity recognition and related taxonomy tasks
• Support prompt evaluation (relevance, factuality, instruction-following, safety)
• Complete computer vision annotation (bounding boxes/segmentation) when assigned
• Document edge cases and propose guideline clarifications; follow versioned specs
• Track annotation guidelines compliance and elevate ambiguous examples

Skills

Data labeling

QA evaluation

Throughput targets

Clear communication

Tools

QA trackers

Labeling tools

Job description

Remote Data Annotator Jobs in Los Angeles (Fully Remote)

Rex.zone is hiring Mid-Senior remote data annotators to create and evaluate training data for AI/ML systems, including NLP, computer vision, and content safety workflows. You will follow detailed guidelines, complete calibrations, and contribute to high-quality datasets used in LLM training pipelines and model evaluation.

What You Will Do

• Apply data labeling rules to text, image, audio, or multimodal samples
• Perform RLHF tasks (preference ranking, pairwise comparisons, rubric-based scoring)
• Conduct QA evaluation through self-checks, peer review, and targeted audits
• Complete NLP labeling such as named entity recognition and related taxonomy tasks
• Support prompt evaluation (relevance, factuality, instruction-following, safety)
• Complete computer vision annotation (bounding boxes/segmentation) when assigned
• Document edge cases and propose guideline clarifications; follow versioned specs
• Track annotation guidelines compliance and elevate ambiguous examples

Required Qualifications

• Mid-Senior experience in data annotation/data labeling/QA evaluation or related operations
• Familiarity with LLM evaluation concepts (rubrics, preference data, error taxonomies)
• Ability to maintain training data quality under throughput targets and feedback cycles
• Strong written communication for documenting rationale and edge cases
• Comfort with web-based labeling tools and QA trackers

Location note:

Work is performed remotely, with hiring focus including Los Angeles candidates.