Senior Machine Learning Engineer – Azure ML, Databricks, MLflow & MLOps
- Toronto, ON, Canada
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Job details
- Posting language
- English
- Posted
Original job description
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 Senior Machine Learning Engineer at Astra North Infoteck will build, deploy and maintain machine learning solutions in the cloud. The role also integrates these models into enterprise applications and works with data scientists and engineers to move AI projects into production.
Requirements
Candidates need hands-on experience putting machine learning models into production on cloud platforms, with expert SQL and Python skills. Strong MLOps, CI/CD and model monitoring experience is essential, and GenAI or LLM experience is an asset.
Skills
- Python
- SQL
- Azure ML
- Databricks
- MLflow
- MLOps
- CI/CD pipelines
- Model deployment
- Model monitoring
- Model lifecycle management
- Feature engineering
- Data preparation
- Machine learning pipelines
- Production support
- Generative AI
- LLM applications
- Agentic AI frameworks
- GenAIOps
- Cloud-native ML platforms
- Enterprise application integration
Categories
- Data & Analytics
- Technology
- Software
Keywords
- Machine Learning Engineer
- MLOps
- Azure ML
- Databricks
- MLflow
- CI/CD
- Python
- SQL
- Model deployment
- Model monitoring
- Feature engineering
- Generative AI
- LLM
- Agentic AI
- GenAIOps
- AI CoE
- Cloud ML
- Machine learning pipelines
Seniority
Senior
Tools
- Azure ML
- Databricks
- MLflow
- Python
- SQL
Languages
- English