Entry Level AI Jobs in Canada

Rex.zone; United States; Sur place; USD 40 000 - 60 000; Plein temps

Résumé du poste

Rex.zone is seeking an Entry Level AI professional to produce high-quality training data through data labeling and evaluations. In this remote full-time position, you will work on various tasks, including RLHF preference ranking, prompt evaluation, and QA evaluations while adhering to detailed guidelines. The ideal candidate will have strong attention to detail and experience in data labeling and content moderation. This role supports distributed AI/ML workflows and contributes to model performance improvement.

Qualifications

• Strong attention to detail and ability to follow detailed guidelines.
• Comfort handling ambiguous cases and explaining labeling rationale.
• Exposure to data labeling platforms, RLHF, and content moderation.

Responsabilités

• Deliver high-accuracy labels using rubric-based decisioning.
• Perform RLHF comparisons and preference judgments.
• Execute prompt evaluation for helpfulness and truthfulness.
• Complete QA evaluation and resolve edge cases.
• Apply content safety labeling policies.
• Annotate NLP datasets for named entity recognition.
• Annotate computer vision datasets using bounding boxes.

Connaissances

Attention to detail

Ability to follow guidelines

Comfort with ambiguity

Experience with data labeling platforms

Knowledge of RLHF

Familiarity with prompt evaluation

Experience with NER

Experience with CV annotation

Content moderation experience

Description du poste

Entry Level AI Jobs in Canada (Remote)

Rex.zone supports practical AI/ML data operations that power LLM training pipelines and model evaluation. In this remote full-time role, you will produce high-quality training data through data labeling, RLHF preference ranking, prompt evaluation, and QA evaluation while following detailed rubrics and policies.

Key Responsibilities

• Deliver consistent, high-accuracy labels using rubric-based decisioning
• Perform RLHF comparisons and preference judgments to support model performance improvement
• Execute prompt evaluation for helpfulness, harmlessness, and truthfulness
• Complete QA evaluation by reviewing outputs and resolving edge cases
• Apply content safety labeling policies (toxic, self-harm, sexual, violence)
• Annotate NLP datasets (named entity recognition, text classification)
• Annotate computer vision datasets (bounding boxes, segmentation)
• Document rationale and exceptions to strengthen guidelines compliance

Qualifications

• Strong attention to detail and ability to follow detailed guidelines
• Comfort handling ambiguous cases and explaining labeling rationale
• Helpful exposure: data labeling platforms, RLHF, prompt evaluation, NER, CV annotation, content moderation
• Ability to work independently in a distributed remote environment

FAQ

Yes—this posting is explicitly Remote for distributed AI/ML data workflows. Country metadata remains US per posting rules.