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Online Machine Learning Jobs in Alberta (NOW HIRING)

Mount Royal University

Data Engineer

Calgary, AB · On-site

... machine learning. Direct experience in data warehousing, ETL/ELT processes, database design with strong verbal and written communication. Must have 5 - 8 years of experience as a data engineer ...

Halliburton

Software Engineer - Landmark

Calgary, AB · On-site

Exposure to integrating machine learning, generative AI, or LLM-based components into application features * Experience mentoring less experienced engineers Energy industry experience is not required ...

Halliburton

Software Engineer - Landmark

Calgary, AB · On-site

Exposure to integrating machine learning, generative AI, or LLM-based components into application features * Experience mentoring less experienced engineers Energy industry experience is not required ...

Crateandbarrel

Sales Associate, C&B

De Winton, AB · On-site

... online pickup in store, in a timely manner, as needed * Assist in preparing the stockroom for ... learning management system, telephone/intercom system, copier, fax machine, SKU and tagger guns ...

Crateandbarrel

Sales Associate

De Winton, AB · On-site

... online pickup in store, in a timely manner, as needed * Assist in preparing the stockroom for ... learning management system, telephone/intercom system, copier, fax machine, SKU and tagger guns ...

Marriott

Maintenance Helper/Groundskeeper

Calgary, AB · On-site

Visually inspect tools, equipment, or machines. Move, lift, carry, push, pull, and place objects ... If you require an accommodation in relation to this job posting, our online application or an ...

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All JobsOnline Machine Learning JobsOnline Machine Learning Jobs in Alberta

Online Machine Learning information

See Alberta salary details

$20.5K

$111.4K

$213K

How much do online machine learning jobs pay per year?

As of Sep 6, 2026, the average yearly pay for online machine learning in Alberta is $111,421.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $156,500.00 per year, depending on experience, location, and employer.

What is online machine learning?

Online machine learning is a method where models are trained incrementally as new data becomes available, rather than being trained all at once on a fixed dataset. This approach is particularly useful in environments where data arrives continuously, such as real-time analytics, recommendation systems, and fraud detection. Online learning algorithms update their knowledge with each new data point, allowing them to adapt quickly to changes and trends. This makes them ideal for applications that require immediate responses and adaptability to evolving data streams.

What are the key skills and qualifications needed to thrive as an online machine learning engineer?

To excel as an Online Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning algorithms, often supported by a relevant degree and experience with streaming data. Familiarity with tools such as Apache Kafka, Spark Streaming, Python, TensorFlow, and real-time data processing frameworks is critical. Problem-solving ability, adaptability, and effective communication are essential soft skills for collaborating with multidisciplinary teams and responding to rapidly changing data. These competencies are crucial for building scalable, responsive models that provide timely insights in dynamic production environments.

How does collaboration typically work between online machine learning engineers and data scientists in a project setting?

Online machine learning engineers often work closely with data scientists to ensure that the models they develop can be effectively deployed and updated in real-time environments. While data scientists may focus on feature engineering, model selection, and initial training using historical data, online machine learning engineers are responsible for integrating these models into production systems and implementing mechanisms for continuous learning from live data streams. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration and ensure that the models remain accurate and efficient as new data arrives.

What is the difference between Online Machine Learning vs Data Scientist?

AspectOnline Machine LearningData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related fields; certifications in ML or data analysisBachelor's or master's in CS, statistics, or related fields; advanced degrees often preferred
Work EnvironmentTech companies, startups, research labs; focus on real-time data processingCorporate, consulting, or research settings; focus on data analysis and modeling
Industry UsageMachine learning applications, AI development, real-time systemsData analysis, predictive modeling, business insights

Online Machine Learning specialists focus on developing algorithms that learn continuously from streaming data, often in real-time environments. Data Scientists analyze large datasets to extract insights, build models, and support decision-making. While both roles require knowledge of machine learning, Online Machine Learning emphasizes real-time data processing, whereas Data Scientists focus on data analysis and modeling for strategic insights.

What are the most commonly searched types of Machine Learning jobs in Alberta?

The most popular types of Machine Learning jobs in Alberta are:

What cities in Alberta are hiring for Online Machine Learning jobs?

Cities in Alberta with the most Online Machine Learning job openings:

Online Machine Learning jobs near you
Infographic showing various Online Machine Learning job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $111,421 per year, or $53.6 per hour.

Data Engineer

Mount Royal University

Calgary, AB • On-site

Full-time

Re-posted 2 days ago

Key responsibilities

  • Design, develop, and implement Microsoft Fabric data lakes, enterprise data warehouse, and BI solutions.

  • Architect and manage cloud data infrastructure on Microsoft Fabric, ensuring high availability, security, and performance.

  • Execute hands-on ELT/ETL and BI development tasks, including ETL job development, data model design, and deployment pipeline creation.

Job description

About the Department The Office of Institutional Research and Planning (OIRP) has primary responsibility for institutional strategic planning, surveying and institutional data analysis at Mount Royal. The Office collects, analyzes, interprets and reports data and information to support decision making, planning and evaluation across the institution. Academic quality assurance is a function of prime importance in a university, and OIRP supports academic units in conducting cyclical program reviews and developing new programs through data, analysis and coordination.

OIRP is responsible for providing quality information and institutional research to inform strategic planning, assessment, development and accountability and for providing leadership in the management of data as a University resource. About the Role This position, reporting to the Director, Institutional Research and Planning, will lead the design, development, and optimization of our Microsoft Fabric data lakes and enterprise data warehouse. In this role, you will be the driving force behind our transition to modern data warehousing solutions leveraging Microsoft Fabric and the broader Azure ecosystem.

The role will be tasked with architecting complex data pipelines, orchestrating ETL/ELT workflows, and integrating disparate data sources-with a specific focus on extracting and transforming data from our Ellucian Banner ERP system. The ideal candidate brings a deep technical mastery of SQL, DevOps, Git, Spark, Python, dataflows, deployment and data pipelines, a passion for performance optimization, and the ability to turn raw data into a strategic asset. Collaboration with colleagues in the Office of Institutional Research and Planning (OIRP) Department, ITS, and engaging experts across other departments are critical components of this role to ensure optimized data integration, high data quality, and fault-tolerant pipelines.

This is a full-time limited term position, working 35 hours per week until December 31, 2028. Responsibilities Data Engineering Design, develop, and implement Microsoft Fabric data lakes, enterprise data warehouse, and BI solutions leveraging various enterprise data warehouse methodologies, models, and technology stack. Architect and manage the cloud data infrastructure on Microsoft Fabric, ensuring high availability, security, and performance.

Execute hands-on ELT/ETL and BI development delivery tasks, specifically; ETL job development, technical data model design, and development of deployment pipelines from dev/UAT environment to production environment. Implement robust monitoring, alerting, and data validation checks to ensure data quality, accuracy and reliability of the data pipelines. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.

Develop data designs, scripts, and code for new projects of moderate to high complexity. Design dimensional and relational structures optimized for reporting and analytics. Data Modelling Understand and gather data and business requirements from various departments and division at MRU and transform them into data warehouse solutions and semantic data models.

Contribute to driving reporting automation and perform quality assurance to support the development of scalable and sustainable data products. Build and architect semantic data models, datasets, and self-service analytical solutions. Develop strategies for data modeling, design, and implementation to meet requirements for metadata management, operational data stores and ELT/ETL environments.

Collaboration and Engagement Engage subject matter experts across OIRP, ITS, and various other departments to provide support and solve complex technical problems and deliver data solutions. Identify cross-institutional issues or problems related to data quality and system integration and recommend solutions and alternatives toward the effective implementation of data quality standards and governance. Collaborate with data specialist, business analysts, management, and other team members to gather requirements and deliver user-centered solutions.

Ensure compliance with institutional and ITS technology standards, policies, and security requirements. Document planned and unplanned changes, and support problem resolution as required. Qualifications A Bachelor degree-preferably in computer science, computer/software engineering or other relevant programs within data engineering, data analysis, artificial intelligence, or machine learning.

Direct experience in data warehousing, ETL/ELT processes, database design with strong verbal and written communication. Must have 5 - 8 years of experience as a data engineer, integrating ERP systems (e.g., Banner, PeopleSoft, Workday), designing data pipelines and building enterprise data warehouses. A combination of education and work experience is required to perform the necessary data requirements gathering and analysis, integration of on-prem data into the cloud lakehouse, design of the cloud enterprise data warehouse and semantic models, and ongoing optimization of data integration processes

Must have experience using Microsoft Fabric technology stack including Pipelines, PySpark, SparkSQL, SparkR, Dataflows, DAX, Notebooks, and Semantic Models - having experience building enterprise data warehouses must be identified in your resume. Fluent in creating data processing frameworks using T-SQL, Python, PySpark, SparkSQL, and Microsoft Fabric technology stack. Experience in delivering data solutions with expert knowledge of CI/CD, DevOps, Git, data structures, data quality management, dimensional modelling, and star-schema design.

Experience with Power Platform (Power Apps, Power Automate) is an asset. Excellent time-management and organizational skills, with the ability to handle conflicting demands and prioritize effectively. Proven abilities to take initiative and be innovative.

Analytical mind with a problem-solving aptitude. Closing Date: Open until a suitable candidate is found A cover letter and resume should be submitted in one .pdf document. Please title your .pdf document as follows: [Last Name], [Requisition Number], [Document Title].pdf (ex

Smith, 4321, CV.pdf).

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