Morningstar Offices

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.

Typical time on-site: 4 days a week

Global Office Locations

Toronto

181 University Avenue, Toronto, ON, Canada, M5H 3M7

Recently posted jobs

2 Days AgoSaved
Hybrid
Toronto, ON, CAN
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Support global demand generation by administering Salesforce and Pardot, maintaining contact data integrity, cleansing and segmenting contact databases, supporting outbound marketing campaigns, analyzing campaign performance, and leading projects to automate workflows and produce reports that demonstrate business impact.
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Design and build cloud-native microservices, REST APIs, and highly available backend services supporting large-scale data requests. Translate business requirements into scalable platform solutions, contribute to architecture modernization, and uphold engineering practices including testing, observability, CI/CD, and code reviews. Troubleshoot production issues, improve reliability, and evaluate emerging data engineering and generative AI technologies. Mentor colleagues and collaborate across technical and business teams.
8 Days AgoSaved
Hybrid
Toronto, ON, CAN
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Build and operate applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, MCP tools, APIs, and governed content-serving layers. The role emphasizes production reliability, provenance, security, cost and latency management, regression detection, and human-reviewed AI outputs. Responsibilities include cloud deployment, structured content modeling, telemetry, governance, mentoring, and collaboration on AI standards. Strong Python, TypeScript, AWS, API, data pipeline, and production LLM experience are required.