Machine Learning Engineer

The total target compensation (TTC) range, including salary and target bonus, is $104,041 - $153,690. This TTC range is applicable to permanent roles only. The actual base salary offered within this range will be determined by the successful candidate’s skills and experience, as well as internal equity.

Empire Life is looking to hire a Machine Learning Engineer to join our Data and Analytics team! We are actively seeking candidates to fill a current, open position.

The Machine Learning Engineer plays a critical role within the AI and Data Science team, responsible for designing, building, deploying, and operationalizing scalable, production-grade machine learning and Generative AI (GenAI) solutions. Operating within a modern Microsoft Azure and Snowflake‑based ecosystem, this role focuses on AI solution architecture, MLOps, robust ML pipelines, observability, and platform scalability. The Machine Learning Engineer bridges the gap between experimentation and enterprise delivery, collaborating closely with Data Scientists, software engineers, and cloud teams to enable secure, reliable AI capabilities—including LLM‑based applications, Retrieval‑Augmented Generation (RAG), intelligent document processing, and agentic AI workflows.

This role reports to the Director of Data and AI strategy.

Why pursue this opportunity

Join a transforming business - we are a medium‑size Canadian company in a stable industry that emphasizes the importance of innovation to use industry‑leading technology.

Play an integral role - this is an opportunity that allows you to grow your skills, while directly contributing to the business unit you are a part of.

The opportunity - collaborate with cross‑functional teams and work on a variety of projects that will keep you engaged and continuously learning.

Hone your skills - this is an opportunity that allows you to grow your technical, and functional skills.

What you’ll be working on

• Collaborate with data scientists, software engineers, cloud infrastructure teams, and business stakeholders to design scalable AI and machine learning solutions aligned with enterprise requirements
• Design, develop, and optimize scalable AI/ML pipelines for data ingestion, feature processing, model training, evaluation, deployment, and monitoring
• Operationalize feature engineering, model serving, vector search, and inference workflows for production AI applications
• Deploy and maintain machine learning and Generative AI solutions in secure, scalable, and highly available production environments
• Implement testing, validation, observability, and monitoring frameworks to support reliability, performance, and governance of AI systems
• Partner with Dev Sec Ops  and cloud engineering teams to automate CI/CD workflows, infrastructure provisioning, model deployment, monitoring, and operational support for AI platforms
• Develop and support Generative AI systems including LLM integrations, retrieval‑augmented generation (RAG), vector databases, orchestration frameworks, and intelligent agents
• Support MLOps, LLMOps, and emerging AIOps practices including model lifecycle management, deployment automation, drift monitoring, evaluation pipelines, logging, and operational governance.

• Master’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field
• 3+ years of working experience with hands‑on industry experience designing, developing, and deploying machine learning or AI‑enabled applications
• Strong understanding of cloud‑native AI and data platforms, particularly within Microsoft Azure ecosystems and enterprise data environments such as Snowflake
• Strong software engineering and system design experience focused on scalable AI/ML applications, distributed systems, APIs, cloud‑native services, or enterprise platform engineering
• Demonstrated experience building and operationalizing machine learning, Generative AI, or intelligent automation solutions in enterprise or production environments
• Strong programming skills in Python and SQL with experience building production‑grade applications, automation workflows, APIs, and AI services
• Familia…