Closed listing
Senior Machine Learning Engineer
- Vancouver, BC, 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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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
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
Build, deploy, and operationalize end-to-end machine learning solutions, including data preparation, feature engineering, model development, monitoring, and production support. Develop scalable ML pipelines and services, integrate solutions into enterprise applications and workflows, and support models throughout their lifecycle.
Requirements
Candidates should have strong hands-on experience taking machine learning models from prototype to production in cloud environments, with expert knowledge of Python and SQL and deep experience with Azure ML, Databricks, MLflow, CI/CD, and MLOps. The role also calls for independent work and effective collaboration; experience with Generative AI, LLM applications, agentic AI frameworks, and GenAIOps is an asset.
Skills
- Machine Learning
- Python
- SQL
- Azure Machine Learning
- Databricks
- MLflow
- CI/CD
- MLOps
- Model Deployment
- Model Monitoring
- Feature Engineering
- Machine Learning Pipelines
- Cloud Computing
- Generative AI
- Large Language Models
- GenAIOps
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
- Science & Research
Keywords
- Machine Learning
- Data Science
- Python
- SQL
- Azure Machine Learning
- Databricks
- MLflow
- CI/CD Pipelines
- MLOps
- Cloud Environments
- Cloud-Native ML Platforms
- Data Preparation
- Feature Engineering
- Model Development
- Model Deployment
- Model Monitoring
- Lifecycle Management
- Production Support
- Scalable ML Pipelines
- ML Services
- Enterprise Applications
- Operational Workflows
- Generative AI
- Large Language Models
- Agentic AI Frameworks
- GenAIOps
- Evaluation
- Automated Deployment
- Proof Of Concept