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