<strong>Remote STEM Jobs in Canada (Full Time)<br><br></strong>Rex.zone connects mid-senior engineers and STEM professionals to real-world AI/ML training workflows, including LLM evaluation, RLHF-style preference ranking, data labeling, QA evaluation, and prompt evaluation. You will help improve model performance by producing and reviewing high-quality training data and enforcing annotation guidelines compliance.<br><br><strong>What You Will Do<br><br></strong><ul><li>Contribute to training data quality through labeling, review, and adjudication</li><li>Perform RLHF-style preference ranking and helpfulness/harmlessness evaluations</li><li>Execute prompt evaluation and response grading for large language model evaluation</li><li>Apply annotation guidelines, document edge cases, and support rubric adherence</li><li>Run QA evaluation workflows, track defects, and recommend process improvements</li><li>Support NLP tasks (e.g., named entity recognition, taxonomy tagging)</li><li>Support computer vision annotation (e.g., bounding boxes, polygons, classification)</li><li>Support content safety labeling (policy categories, risk scoring, refusals)</li><li>Collaborate with teams across AI labs, tech startups, annotation vendors, and BPO operations<br><br></li></ul><strong>Required Qualifications<br><br></strong><ul><li>Mid-senior experience in STEM or engineering</li><li>Strong analytical writing and attention to detail for evaluation rubrics</li><li>Familiarity with AI/ML concepts, LLM behavior, and model failure modes</li><li>Experience with data labeling, QA evaluation, or guideline-driven review</li><li>Ability to work full-time remotely with reliable internet and secure work practices<br><br></li></ul><strong>Preferred Qualifications<br><br></strong><ul><li>Exposure to RLHF, prompt evaluation, and rubric-based grading</li><li>Experience with NLP and/or computer vision annotation</li><li>Experience with content safety labeling and policy enforcement</li><li>Comfort using annotation platforms, spreadsheets, and issue trackers</li><li>Ability to mentor peers on annotation guidelines compliance and training data quality<br><br></li></ul><strong>How To Apply<br><br></strong>Apply via Rex.zone and highlight your STEM/engineering background, guideline-driven work, and examples that improved training data quality or model performance.