AI Engineer Jobs in Canada
• *Overview**
AI Engineer roles focused on building, deploying, and evaluating AI/ML systems for real-world LLM training pipelines and applied ML products. These are remote, full-time, mid-senior positions spanning NLP, computer vision, and content safety, with strong emphasis on evaluation, data quality, and production reliability.
• *What You Will Do
• Design and ship AI/ML features from prototype to production using reproducible training and inference workflows
• Build evaluation pipelines for LLM evaluation, prompt evaluation, and regression testing
• Partner with data teams on data labeling strategy, guideline compliance, and training data quality audits
• Implement QA evaluation and error analysis to drive measurable model performance improvements
• Develop RLHF-style feedback loops (where applicable) to improve helpfulness, safety, and instruction following
• Integrate NLP components such as named entity recognition, classification, retrieval-augmented generation, and prompt templates
• Support computer vision annotation and multimodal iteration when required
• Monitor production metrics, latency, and drift; document experiments, model cards, and evaluation reports
• *What We’re Looking For
• Mid-senior experience delivering production ML systems end-to-end
• Strong Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, JAX)
• Hands-on experience with LLMs, NLP, and model evaluation methodologies
• Understanding of data labeling workflows, QA evaluation, and annotation quality impacts
• Practical MLOps knowledge (CI/CD for ML, model registries, monitoring)
• Strong collaboration and communication skills across engineering and data operations
• *Compensation**
Competitive base pay: $30–$50 per hour (HOURLY).
AI Engineer roles focused on building, deploying, and evaluating AI/ML systems for real-world LLM training pipelines and applied ML products. These are remote, full-time, mid-senior positions spanning NLP, computer vision, and content safety, with strong emphasis on evaluation, data quality, and production reliability.
• *What You Will Do
• Design and ship AI/ML features from prototype to production using reproducible training and inference workflows
• Build evaluation pipelines for LLM evaluation, prompt evaluation, and regression testing
• Partner with data teams on data labeling strategy, guideline compliance, and training data quality audits
• Implement QA evaluation and error analysis to drive measurable model performance improvements
• Develop RLHF-style feedback loops (where applicable) to improve helpfulness, safety, and instruction following
• Integrate NLP components such as named entity recognition, classification, retrieval-augmented generation, and prompt templates
• Support computer vision annotation and multimodal iteration when required
• Monitor production metrics, latency, and drift; document experiments, model cards, and evaluation reports
• *What We’re Looking For
• Mid-senior experience delivering production ML systems end-to-end
• Strong Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, JAX)
• Hands-on experience with LLMs, NLP, and model evaluation methodologies
• Understanding of data labeling workflows, QA evaluation, and annotation quality impacts
• Practical MLOps knowledge (CI/CD for ML, model registries, monitoring)
• Strong collaboration and communication skills across engineering and data operations
• *Compensation**
Competitive base pay: $30–$50 per hour (HOURLY).