Lead Applied AI and Data Scientist

Location: Vancouver, British Columbia, Canada

Salary: $113,000–$152,000 CAD annually plus variable bonus

Company

hirify.global is an enterprise software company developing AI-driven solutions for customers worldwide, including the hirify.global Copperleaf capital-planning platform.

What you will do

• Establish and lead the applied AI and data science practice within the AI Engineering & Transformation pillar.
• Build curated datasets, domain-model training pipelines, and reusable modeling and evaluation standards.
• Design and productionize forecasting, anomaly detection, classification, clustering, causal, risk, and signal models.
• Guide LLM and agentic AI work, including RAG, grounding, fine-tuning, distillation, embeddings, semantic search, and model routing.
• Build quantitative evaluation frameworks covering accuracy, repeatability, hallucination rates, grounding, citations, and human feedback.
• Own model lifecycle operations, including deployment, A/B testing, versioning, drift detection, retraining, monitoring, and cost telemetry.

Requirements

• Advanced degree in a quantitative field such as computer science, statistics, mathematics, physics, or engineering, or equivalent hands-on experience.
• Deep applied data science and machine learning experience across classical ML and generative AI or LLM systems.
• Experience with rigorous ML, LLM, and agent evaluation, including LLM-as-judge, programmatic evaluators, statistical thresholds, and human-in-the-loop feedback.
• Hands-on experience with fine-tuning, distillation, RAG, grounding, prompt optimization, embeddings, semantic search, and agentic frameworks.
• Production ML experience covering MLOps, deployment, model versioning, drift monitoring, and retraining.
• Advanced Python and SQL skills, familiarity with ML libraries, major LLM APIs, open-weight models, and cloud platforms; Azure is preferred.

Nice to have

• Experience establishing a data science, ML, or applied AI function and mentoring others.
• Experience in regulated, asset-intensive industries such as utilities, energy, mining, or oil and gas.
• Experience with causal inference, benchmarking, peer indices, network-effect data products, or governance-aware AI.
• Databricks experience.

Culture & Benefits

• Flexible paid time off, including sick and holiday leave.
• Medical, dental, and vision insurance.
• RRSP matching, life insurance, and disability benefits.
• Community involvement and volunteering events.
• Flexible and hybrid work opportunities with an emphasis on inclusive workplace experiences.