- Employment type
- Full-time · On-site
- Posted
- November 9, 2026
- Province
- Ontario (ON)
Hiring confidence: Sparse posting · 33/100
This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored
Job Overview
This role is based in Ontario. Waabi is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in Ontario
Average salary for Senior / Staff ML Ops Engineer in Ontario
We do not have a salary benchmark for this title in Ontario yet. The posting does not state a salary either.
NOC code
This posting has not been matched to a NOC 2021 unit group yet. Use the NOC finder to identify the code from the duties listed above.
Typical qualifications for Canadian employers
- Significant experience in MLOps or ML infrastructure roles
- Strong software engineering fundamentals
- Experience with machine learning frameworks and tools
- Knowledge of cloud platforms (AWS, GCP, or Azure)
- Experience with containerization and orchestration
Fit check
Is this role right for you?
Top skills this posting asks for:
- Machine Learning Operations
- MLOps
- ML Infrastructure
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What you'll do
- Design and implement ML infrastructure and pipelines
- Manage ML model deployment and versioning systems
- Develop tools and platforms for ML teams
- Optimize ML workflows and computational efficiency
- Ensure reliability and scalability of ML systems
- Monitor and troubleshoot ML production systems
- Collaborate with data scientists and engineers
- Implement best practices for ML operations
What you'll need
- Significant experience in MLOps or ML infrastructure roles
- Strong software engineering fundamentals
- Experience with machine learning frameworks and tools
- Knowledge of cloud platforms (AWS, GCP, or Azure)
- Experience with containerization and orchestration
- Understanding of ML model lifecycle and deployment
- Experience with monitoring and observability tools
- Excellent communication and collaboration skills