Machine Learning Engineer (AI)

Salary: $92,3000–$151,400 CAD.

Company

hirify.global is a global insurance provider offering commercial property-casualty insurance, risk management products, and services across more than 25 industries.

What you will do

• Design, develop, productionize, and operate scalable machine learning and AI solutions across applied AI, generative AI, data and ML platforms, and MLOps.
• Build predictive models, feature pipelines, training and inference workflows, LLM services, RAG pipelines, and controlled agentic workflows.
• Engineer enterprise-scale data, feature, platform, CI/CD, infrastructure, model registry, and deployment capabilities.
• Evaluate models, retrieval, answers, safety, groundedness, latency, reliability, cost, and business outcomes.
• Monitor data quality, performance, drift, security, and production reliability while troubleshooting issues and implementing retraining or redeployment workflows.
• Collaborate with Data Engineering, Data Science, Architecture, Governance, Security, and business teams; document models, data, prompts, approvals, lineage, and evaluation records.

Requirements

• Python and SQL skills.
• Software engineering fundamentals, including Git, APIs, testing, and CI/CD.
• Understanding of machine learning concepts and the model-development lifecycle.
• Experience with data processing and analytical workloads.
• Experience in cloud-based development environments.
• Understanding of reliable, maintainable, production-ready solutions.
• For the relevant specialization, experience may include statistical machine learning, feature engineering, model evaluation, time-based validation, leakage prevention, imbalanced datasets, calibration, experiment tracking, and batch or real-time inference.
• For the relevant specialization, experience may include RAG, embeddings, vector indexes, BM25, semantic or hybrid search, retrieval and LLM evaluation, prompt engineering, FastAPI, or managed AI platforms.
• For the relevant specialization, experience may include Databricks, Spark or PySpark, Delta Lake, batch or streaming architectures, feature management, data-quality testing, lineage, cloud storage or compute, CI/CD, and infrastructure as code.
• For the relevant specialization, experience may include MLflow, Azure Machine Learning, Azure DevOps, GitHub Actions, REST APIs, Docker, Kubernetes, Terraform, model registries, and production observability.

Nice to have

• Databricks, MLflow, and Apache Spark or PySpark.
• Microsoft Azure or equivalent AWS or Google Cloud technologies.
• Azure DevOps or GitHub.
• Docker and containerized applications.
• REST APIs.
• scikit-learn, PyTorch, TensorFlow, or comparable machine learning and deep-learning frameworks.
• Azure OpenAI or comparable managed AI platforms.
• RAG, embeddings, retrieval, and LLM evaluation.
• Infrastructure as code, Kubernetes, and production observability.
• Security, privacy, Responsible AI, and model governance in a regulated environment.

Culture & Benefits

• Collaborative, values-driven, diverse, inclusive, equitable, and supportive workplace.
• Comprehensive health and wellness benefits.
• Minimum four weeks of vacation annually and four personal days each year.
• Ongoing learning and development opportunities.
• Opportunities to support and give back to communities.
• Accessible and barrier-free workplace with accommodation support available.