Closed listing
Senior Machine Learning Engineer – Azure ML, Databricks, MLflow & MLOps
- Toronto, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Posting language
- English
- Posted
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Original job description
Archived listing. The details below describe a past opening.
Senior Machine Learning Engineer – Azure ML, Databricks & MLOps
Skills and Responsibilities:
- We are looking for an experienced Senior Machine Learning Engineer to support the AI CoE’s Machine Learning and Data Science initiatives.
- The ideal candidate will have strong hands-on experience building, deploying, and operationalizing machine learning solutions in cloud environments, with expert knowledge of SQL and Python and deep experience with Azure ML, Databricks, MLflow, CI/CD pipelines, MLOps, model deployment, monitoring, and lifecycle management.
- This is a highly technical, hands-on role focused on delivering end-to-end ML solutions, including data preparation, feature engineering, model development, deployment, monitoring, and ongoing production support.
- The role requires proven experience taking models from prototype to production, building scalable ML pipelines and services, and integrating machine learning solutions into enterprise applications and operational workflows.
- Experience with cloud-native ML platforms, automated deployment processes, and production support is essential.
- Experience with Generative AI, LLM applications, agentic AI frameworks, and GenAIOps practices - including evaluation, monitoring, deployment, and lifecycle management of GenAI solutions - would be considered an asset.
- In addition to technical depth, we are looking for someone who can work independently, collaborate effectively with data scientists and engineers, and help accelerate the delivery of enterprise AI solutions from proof of concept through production deployment.
More about this job
Responsibilities
The role focuses on building, deploying, and operationalizing end-to-end machine learning solutions within the AI CoE. Responsibilities include data preparation, model development, and providing ongoing production support for enterprise AI applications.
Requirements
Candidates must have expert knowledge of Python, SQL, and cloud-native ML platforms like Azure ML and Databricks. Proven experience in taking models from prototype to production and implementing MLOps practices is essential.
Skills
- Azure ML
- Databricks
- MLflow
- MLOps
- Python
- SQL
- CI/CD Pipelines
- Model Deployment
- Model Monitoring
- Lifecycle Management
- Feature Engineering
- Generative AI
- LLM Applications
- Agentic AI Frameworks
- GenAIOps
- Data Preparation
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Software
- Technology
- Engineering
- Consulting
Keywords
- Azure ML
- Databricks
- MLflow
- MLOps
- Python
- SQL
- CI/CD
- Model Deployment
- Model Monitoring
- Lifecycle Management
- Generative AI
- LLM
- Agentic AI
- GenAIOps
- Feature Engineering
- Cloud-native
- Enterprise AI
- Data Science
- Machine Learning Engineer
- AI CoE