MLOps Engineer (Azure ML Pipeline) [BHJOB13022_13671]

Ignite Technical; Richmond; Hybrid; CAD 90,000 - 130,000; Full time

Job summary

Ignite Technical is seeking an MLOps Engineer for a 7-month hybrid contract in Richmond, BC. The successful candidate will be responsible for deploying and maintaining machine learning models using Azure ML, integrating MLOps into the DevOps lifecycle, and ensuring model reliability. Candidates must possess a bachelor's degree and significant experience in MLOps or DevOps, particularly within Azure environments.

Qualifications

• 5–7 years of MLOps or DevOps experience.
• Proven experience deploying ML solutions in Azure.
• Strong knowledge of Azure ML, DevOps, Python, SQL, and ETL tools.

Responsibilities

• Deploy ML models into production using Azure ML.
• Integrate MLOps practices within the DevOps lifecycle.
• Monitor and improve models incorporating drift detection.

Skills

Azure ML

DevOps

Python

SQL

ETL tools

Education

Bachelor’s degree in a relevant field

Job description

On behalf of our Public Sector Client, Ignite Technical Resources is recruiting for an MLOps Engineer (Azure ML Pipeline) to join our Client's team on a contract basis. This role is Hybrid,and the Client is based in Richmond, BC.

Summary of the Role:
The MLOps Engineer will be responsible for deploying and maintaining analytical and machine learning models using Azure Machine Learning across environments. This includes developing scalable machine learning pipelines, ensuring model reliability and performance, and collaborating with cross-functional teams to implement MLOps best practices.

Duties & Responsibilities:

• Deploy ML models into production using Azure ML and implement pipelines across environments.
• Integrate MLOps practices within the DevOps lifecycle, including CI/CD automation.
• Develop scalable tools for ML training and inference, integrating with existing infrastructure.
• Monitor and improve models without affecting performance, incorporating drift detection.
• Provide support for production processes and perform root cause analysis.
• Collaborate with Cloud Ops on settings, architecture, and cost monitoring.
• Lead requirements gathering and implementation for ML production releases.

Core Requirements:

• Bachelor’s degree in a relevant field with 5–7 years of MLOps or DevOps experience.
• Proven experience deploying ML solutions in Azure environments.
• Strong knowledge of Azure ML, DevOps, Python, SQL, and ETL tools.
• Ability to build and manage Azure ML pipelines and automate coding patterns.
• Skilled in diagnosing production issues and implementing preventative solutions.

Desired Skills & Experience:

• Experience with Agile methodologies and MLOps governance.
• Prior involvement in productionizing ML models independently.
• Familiarity with cloud cost estimation and monitoring tools.
• Expertise in monitoring systems for model drift and production failures.
• Strong cross-functional collaboration on MLOps best practices.

Terms
This is a 7-month contract role requiring a hybrid work arrangement with 3 days onsite per week in Richmond, BC. The onsite requirement is non-negotiable. Before receiving an offer, the successful candidate must complete a reference check, background check, and sign a training agreement.

About Ignite Technical: Based in Vancouver and proudly Canadian, Ignite Technical Resources has been providing Top Technical Talent to organizations across Canada since 2005.

Equal Opportunity Employer: Ignite Technical is an equal opportunity employer and is committed to providing equal employment opportunities to all individuals regardless of race, color, religion, sex, sexual orientation, disability, gender identity, national origin, or age.

Work Permits: Please note that Ignite’s Clients require all interested candidates to obtain the necessary work permits from the Government of Canada prior to submitting an application. This position is open exclusively to individuals residing in Canada and legally authorized to work in Canada. Applications not meeting these criteria will not be considered.

Further Consideration: We receive a high volume of applications and are only able to contact candidates who are selected for further consideration.

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