Posted 2 months ago
Senior Machine Learning Engineer – Azure ML, Databricks, MLflow & MLOps
@ Astra North Infoteck Inc.
Toronto, Ontario
Overview
Astra North Infoteck Inc. is hiring a Senior Machine Learning Engineer to support the AI CoE's machine learning and data science initiatives. The role takes models from prototype to production, covering data preparation, feature engineering, deployment, monitoring and ongoing production support on cloud platforms.
Responsibilities:
- Build and deploy ML solutions end to end
- Develop scalable ML pipelines and services
- Monitor and provide production support for models
- Integrate ML solutions into enterprise workflows
Requirements summary:
- Hands-on experience deploying ML to production
- Expert SQL and Python skills
- Experience with Azure ML, Databricks and MLflow
- Strong CI/CD and MLOps practice
- GenAI and LLM experience is an asset
Tools & skills
Source and dates
Source type not verified · zoho
- Employer posting date
- 2026-08-30
- First seen by our source
- 2026-10-11
- Source record updated
- 2026-10-11
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Astra North Infoteck Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 427 |
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.
Journal
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