ML Engineer

About the Company

Our client, a major Canadian insurance and financial services organization known for its large national presence and commitment to modernization, is seeking to hire an ML Engineer (hybrid, 2 days/week in office).

• Design, build, and operate production-grade ML platforms on Databricks.
• Implement end-to-end MLOps workflows: experimentation – registry – deployment – monitoring.
• Develop CI/CD pipelines for ML (code, data, models) using tools like Git Hub Actions or Azure Dev Ops.
• Operationalize model governance (mlflow tracking, registry, versioning, lineage).
• Deploy models for batch and real-time scoring, ensuring safe deployment and rollback strategies.
• Implement observability and monitoring for model performance, data drift, and operational health.
• Create standards, reusable templates, and documentation for consistent ML delivery.
• Partner with Data Scientists, Data Engineers, and Architects to enable platform capabilities at scale.

• Hands‑on experience with Databricks in production (work spaces, workflows, cluster policies).
• Strong experience with mlflow (tracking, registry, packaging, deployment).
• Proven track record in CI/CD for ML and automated ML lifecycle.
• Proficiency in Python and solid software engineering practices (testing, packaging, code reviews).
• Databricks Unity Catalog and governance patterns.

• Familiarity with Databricks Asset Bundles (DABs) or MLOps Stacks.
• Knowledge of feature store patterns, streaming/near‑real‑time scoring.
• Banking, telecom, or insurance industry experience.

$100,000 - $150,000/year

Click the “Apply Now” button and follow the instructions to submit your resume. Please note that we only accept documents in MS Word or Rich Text formats.

When referring to this job, quote #466224.

You must currently reside within the Greater Toronto Area and be permitted to work in Canada to be considered for this opportunity.

A recruiter will be in touch with you if your profile meets our client’s requirements for this role.