AI Research Canada; Remote

About The Role

This Remote,  AI Research position supports end-to-end research and applied experimentation for modern AI systems, including LLM training pipelines, RLHF evaluation, prompt evaluation, and model performance improvement. You will design experiments, define evaluation protocols, and improve evaluation rigor through robust measurement, dataset strategy, and QA evaluation workflows.

• Develop and run AI research experiments across NLP, computer vision, and multimodal settings
• Design evaluation harnesses for large language model evaluation, including offline/online metrics
• Define RLHF and preference modeling evaluation protocols (rubrics, sampling plans, inter-rater reliability)
• Partner with data labeling teams to improve training data quality and annotation guidelines compliance
• Perform error analysis, ablation studies, and prompt evaluation to identify failure modes
• Build reproducible pipelines for dataset curation, data labeling audits, and QA evaluation
• Translate research findings into engineering-ready requirements and measurable acceptance criteria
• Support content safety labeling strategy and risk analysis for model outputs

• AI research and machine learning research fundamentals
• Experience with large language models and model evaluation
• Hands‑on RLHF concepts (preference data, reward modeling, evaluation)
• Strong experiment design and statistics basics
• Familiarity with training data quality practices and dataset documentation
• NLP and/or computer vision domain knowledge
• Ability to collaborate cross‑functionally with engineering and data operations

$30–$50 per hour (HOURLY)

Apply via Rex.zone with a resume and relevant research artifacts (papers, technical reports, repositories, or evaluation write-ups) demonstrating model performance improvement.