Machine Learning Scientist II - Marketing Optimization (AI)

Location: Toronto, Canada; candidates must be based in or plan to relocate to Toronto, ON. Hybrid schedule with onsite work Tuesday–Thursday and remote work Monday and Friday.

Annual base pay: CAD 168,960–188,776.50, excluding potential equity, bonuses, commissions, and other compensation.

Company

hirify.global is an online retail platform that uses machine learning and AI to improve how customers shop for their homes.

What you will do

• Design, build, deploy, and refine large-scale machine learning models and algorithmic decision-making systems.
• Develop GenAI and LLM applications using reinforcement learning to optimize content across marketing channels.
• Architect GenAI-driven content optimization infrastructure while balancing cost and performance.
• Research content-generation applications for long-form text and images.
• Build agentic AI solutions that generate insights and optimize channel analytics workflows.
• Enable non-Science stakeholders to optimize content through centralized algorithms and production systems.

Requirements

• PhD with at least 0 years of experience, or 2+ years of industry experience with an MS, or 4+ years with a BS in a quantitative STEM field.
• Proficiency in Python or another high-level programming language.
• Strong theoretical understanding and hands-on experience deploying machine learning solutions into production.
• Strong written and verbal communication skills, including the ability to explain conclusions to non-experts.
• Intellectual curiosity and enthusiasm for continuous learning.

Nice to have

• Experience with the Python machine learning ecosystem, including NumPy, pandas, scikit-learn, or XGBoost.
• Experience with Apache Spark, Spark SQL, or MLlib/Spark ML.
• Familiarity with GCP, AWS, or Azure.
• Familiarity with machine learning development frameworks and orchestration tools such as Airflow, Kubeflow, or MLflow.

Culture & Benefits

• Cross-functional and collaborative work focused on production machine learning systems with real-world impact.
• Opportunities for continuous learning, creative problem-solving, and work on dynamic technical challenges.
• Comprehensive medical, financial, and additional employee benefits.
• Reasonable accommodations are available for qualified individuals with disabilities during the application and interview process.