Remote Data Annotator Jobs Toronto

About Rex.zone Rex.zone is hiring Toronto-based candidates for full-time remote data annotation and data labeling work that improves training data quality for AI/ML systems. You will support real-world LLM training pipelines through evaluation, QA, and careful rubric-driven judgments.

About Rex.zone Rex.zone is hiring Toronto-based candidates for full-time remote data annotation and data labeling work that improves training data quality for AI/ML systems. You will support real-world LLM training pipelines through evaluation, QA, and careful rubric-driven judgments.

About The Role As a Remote Data Annotator, you will create and evaluate labeled datasets used in large language model evaluation, RLHF workflows, NLP tasks (e.g., named entity recognition), computer vision annotation, and content safety labeling. You will follow strict annotation guidelines compliance, document edge cases, and collaborate asynchronously to improve model performance outcomes.

Key Responsibilities Produce high-accuracy data labeling for text, image, and mixed-modality tasks

Execute RLHF comparisons, preference judgments, response scoring, and rationale capture

Perform prompt evaluation and rubric grading for helpfulness, correctness, and policy adherence

Complete NLP annotations such as named entity recognition, classification, and entity linking using defined ontologies

Support computer vision annotation including bounding boxes, polygons, segmentation masks, and attribute tagging

Conduct content safety labeling across harassment, self-harm, sexual content, violence, and sensitive traits

Run QA evaluation using gold sets, spot checks, reviewer audits, inter-annotator agreement, and defect taxonomies

Report ambiguous examples, escape edge cases, and propose guideline clarifications to reduce label noise

Required Qualifications Mid-Senior experience in data annotation, data labeling, QA evaluation, or LLM evaluation

Ability to interpret detailed rubrics and maintain consistent decision-making

Strong written communication for edge-case documentation and rationale writing

Comfort working with structured taxonomies (NER, content safety, prompt evaluation)

Reliability in meeting throughput and quality targets in a remote environment

Tools & Quality Standards You will work in web-based labeling platforms and evaluation consoles using versioned guidelines and task queues. Quality is measured through sampling, consensus review, inter-annotator agreement checks, and defect tagging. You must be able to handle potentially sensitive content and follow confidentiality requirements.

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