AI Training Jobs in Canada

AI Training Jobs in Canada focus on building and evaluating AI/ML training data for LLM training pipelines on Rex.zone. In this full-time remote role, you will perform data labeling, RLHF ranking, prompt evaluation, and QA evaluation to improve model performance and training data quality. You will follow annotation guidelines compliance, support NLP and computer vision annotation tasks, and contribute to content safety labeling workflows used by AI labs, tech startups, and annotation vendors.

LinkedIn Job Metadata — AI Training Jobs in Canada

About the Role

You will support end-to-end AI training workflows by labeling and evaluating text, image, and multimodal data used in large language model evaluation and model training. Typical tasks include RLHF preference ranking, prompt response evaluation, content policy checks, named entity recognition, and computer vision annotation while maintaining training data quality and consistent rubric adherence.

What You Will Do

["Perform data labeling for NLP, LLM, and computer vision annotation tasks","Execute RLHF ranking and pairwise preference judgments to improve model performance","Run QA evaluation checks and apply annotation guidelines compliance to reduce label noise","Conduct prompt evaluation and response grading for helpfulness, correctness, and safety","Apply content safety labeling for policy categories such as harassment, self-harm, and adult content","Document edge cases, write clear rationales, and escalate ambiguous examples to leads","Collaborate asynchronously with cross-functional teams across AI labs, tech startups, BPOs, and annotation vendors"]

Required Qualifications

["Mid-Senior experience in AI/ML data operations, evaluation, or large-scale annotation programs","Strong analytical writing and rubric-driven decision-making for prompt evaluation and RLHF tasks","Familiarity with LLM training pipelines, dataset QA, and common sources of annotation error","Experience with NLP concepts (classification, NER) and/or computer vision annotation workflows","Ability to maintain high agreement rates, follow SOPs, and meet throughput targets in remote settings"]

Preferred Qualifications

["Hands-on experience with RLHF, reward modeling datasets, or LLM evaluation frameworks","Background in content moderation or content safety labeling programs","Experience building or improving annotation guidelines and calibration processes","Comfort working with multilingual data and region-specific context for Canada-focused tasks","Knowledge of QA sampling, inter-annotator agreement, and error taxonomy"]

Workflow and Tools

["Queue-based task routing with clear SLAs and audit trails","Calibration sessions to align on annotation guidelines compliance","Gold-standard checks, spot audits, and feedback loops for training data quality","Issue tracking for edge cases and guideline updates","Secure remote work practices and privacy-first handling of sensitive data"]

Employment Details

["Remote: Remote","Employment Type: FULL_TIME","Experience Level: Mid-Senior","Compensation Range: 63360 to 126720 USD per year","Industry: Technology","Job Function: Engineering"]

How to Apply on Rex.zone

["Visit Rex.zone and search: AI Training Jobs in Canada","Review role requirements and confirm availability for full-time remote work","Submit your application and complete any evaluation tasks","Track application status and new remote, contract, freelance, entry-level, and senior AI training listings on Rex.zone"]

Frequently Asked Questions

Q: What are AI training jobs in Canada?
They are roles focused on preparing and evaluating training data for AI systems, including data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, and content safety labeling used in LLM training pipelines.
Q: Is this role remote?
Yes. The position is explicitly marked Remote and is designed for remote execution with asynchronous collaboration and secure data handling.
Q: What domains will I work on?
You may work across NLP tasks like named entity recognition, LLM response evaluation and RLHF, plus computer vision annotation and content safety labeling depending on project needs.
Q: What does success look like in this role?
Consistently high training data quality, strong agreement with guidelines, accurate QA evaluation outcomes, clear rationales for edge cases, and measurable model performance improvement signals from evaluation results.
Q: Are contract or freelance options available?
This listing is FULL_TIME, but Rex.zone may also feature remote contract, freelance, entry-level, and senior roles depending on employer demand.
Q: What skills are most important?
RLHF, data labeling, QA evaluation, prompt evaluation, annotation guidelines compliance, NLP and/or computer vision annotation, content safety labeling, and strong written reasoning for large language model evaluation.

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