Posted 2 months ago
Senior Machine Learning Engineer
@ Staffmax
Toronto, Ontario
Overview
Staffmax is hiring a Senior Machine Learning Engineer in Toronto to join its AI Centre of Excellence. The role is hybrid, full-time, with a salary of about $110K, and centres on building, deploying and supporting ML solutions in cloud environments.
Responsibilities:
- Build and deploy end-to-end machine learning solutions
- Develop and maintain MLOps and CI/CD pipelines
- Monitor model performance and provide production support
- Work with Azure ML and Databricks to operationalize ML
Requirements summary:
- Strong Python and SQL experience
- Hands-on Azure ML and Databricks experience
- Experience with MLflow and MLOps
- Experience deploying ML models to production
Tools & skills
Source and dates
Employer career site / ATS feed · careerpage
- Employer posting date
- 2026-09-21
- 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 | Data & analytics |
| Hours per week | 40 (estimated) |
| Travel | air: none · ground: none |
| 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.
Staffmax
| Field | Value |
|---|---|
| Open jobs on Jobsy | 143 |
Location: Toronto, ON
Work Model: Hybrid
Job Type: Full-Time
Salary: 110K
About the Role
We are looking for a Senior Machine Learning Engineer to join the AI Centre of Excellence (AI CoE) and support enterprise Machine Learning and Data Science initiatives.
This is a hands-on technical role focused on building, deploying, and supporting machine learning solutions in cloud environments.
The ideal candidate will have strong experience with Python, SQL, Azure ML, Databricks, MLflow, MLOps, CI/CD, and model deployment.
What You'll Do
- Build and deploy end-to-end machine learning solutions.
- Prepare data and perform feature engineering and model development.
- Build scalable ML pipelines and automation workflows.
- Deploy ML models into production and provide ongoing support.
- Monitor model performance and manage the ML lifecycle.
- Develop and maintain MLOps and CI/CD pipelines.
- Work with Azure ML and Databricks to operationalize ML solutions.
- Integrate ML models into enterprise applications and business workflows.
- Work closely with Data Scientists, Data Engineers, and other technical teams.
- Troubleshoot production issues and continuously improve ML solutions.
- Help move AI/ML projects from proof of concept to production.
Required Skills & Experience
- Strong hands-on experience with Python and SQL.
- Experience building and deploying machine learning models.
- Strong experience with Azure ML.
- Hands-on experience with Databricks.
- Experience with MLflow.
- Strong understanding of MLOps and ML lifecycle management.
- Experience building CI/CD pipelines for ML solutions.
- Experience with model deployment, monitoring, and production support.
- Strong understanding of data preparation and feature engineering.
- Experience working with cloud-based ML platforms.
- Ability to work independently and collaborate with Data Scientists and Engineers.
Nice to Have
- Experience with Generative AI and LLM applications.
- Experience with Agentic AI frameworks.
- Knowledge of GenAIOps, including AI evaluation, monitoring, deployment, and lifecycle management.
- Experience integrating AI solutions into enterprise applications.
Journal
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