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Online Machine Learning Jobs in Alberta (NOW HIRING)

Machine Learning Engineer Calgary, AB, Canada Full-time Company Description Viridien is a global technology and HPC leader that provides data, products, services and solutions in Earth science, data ...

Machine Learning Engineer - Contract Length: 1 year (potential for extension) Location: Calgary (Hybrid, 2 days onsite) Your New Company Join a leading enterprise organization undergoing a major ...

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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 Jun 16, 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 jobs pay $2000 a day?

In the field of online machine learning, highly specialized roles such as AI consultants, data science experts, or machine learning engineers working on large-scale projects can earn around $2,000 per day, especially with extensive experience, advanced skills in programming and algorithms, and working as independent contractors or consultants. These roles often require strong expertise in tools like Python, TensorFlow, or cloud platforms, and may involve project-based or freelance work with flexible schedules.

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 is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as AI research directors, chief AI officers, or senior machine learning executives, often requiring advanced expertise, leadership skills, and extensive experience. These positions usually involve strategic decision-making, overseeing AI projects, and may require knowledge of deep learning, data science, and relevant tools like TensorFlow or PyTorch.

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 are the key skills and qualifications needed to thrive as an Online Machine Learning Engineer, and why are they important?

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.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in algorithms and data modeling, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or executive-level roles.

Which 3 jobs will survive AI?

Online machine learning specialists, data scientists, and AI ethics professionals are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require advanced skills in programming, statistical analysis, and domain knowledge, making them less susceptible to automation. Continuous learning and certification in relevant tools like Python, TensorFlow, or cloud platforms can enhance job security in this field.
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 are popular job titles related to Online Machine Learning jobs in Alberta? For Online Machine Learning jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Online Machine Learning jobs in Alberta look for? The top searched job categories for Online 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:
Infographic showing various Online Machine Learning job openings in Alberta as of June 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $111,421 per year, or $53.6 per hour.

Machine Learning Engineer

Viridien

Calgary, AB • On-site

Full-time

Posted 13 days ago


Job description

Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.

Machine Learning Engineer

Calgary, AB, Canada

Full-time

Company Description

Viridien is a global technology and HPC leader that provides data, products, services and solutions in Earth science, data science, sensing and monitoring. Our unique portfolio supports our clients in efficiently and responsibly solving complex digital, energy transition, natural resource, environmental, and infrastructure challenges for a more sustainable future.

Job Description

Viridien is looking for a Machine Learning (ML) Engineer to help us create artificial intelligence systems and tools. Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. Strong skills in statistics and programming, as well as knowledge of data science and software engineering. As an integral member of our team, we highly encourage the contribution of ideas and drive in the generation of new concepts to maintain our outstanding leadership position for technology and service delivery in the marketplace.

Must be legally authorized to work in Canada.

Qualifications

Preferred Education

Degree in Computer Science, Mathematics, Physics, Electrical Engineering, or other related technical disciplines.

Key Skills & Competencies

  • Passion and aptitude for programming and technology
  • Enthusiasm for analytical and problem-solving challenges
  • Strong enterprise project experience with Machine Learning and AI
  • Strong programming skills within one or more of these development languages - C / C++ / R / Java / Python
  • Good experience with Large Language Model technologies
  • Experience within Data Engineering/Data Structuring
  • Experience creating Machine Learning Algorithms and/or Libraries.
  • Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch)
  • Proficiency to design, build, test, and support innovative solutions.
  • Ability to define and manage project deadlines and balance workloads across a wide variety of projects.
  • Effective communication skills to keep all stakeholders regularly informed on progress.
  • Drive to innovate and have fun through collaboration and generation of ideas which lead to enhancements of our workflows.
  • Enthusiastic attitude towards learning and flexibility to adapt to new challenges or changes in direction.

Other Skills/Experience:

  • Data Visualization
  • Predictive Analysis
  • Statistical Modeling
  • Data Mining
  • Clustering & Classification
  • Data Analytics
  • Quantitative Analysis
  • Web Scraping
  • Model Development

Responsibilities:

  • Design machine learning systems
  • Collaborate with stakeholders and technology team to efficiently develop AI solutions.
  • Research and implement appropriate ML algorithms and tools.
  • Develop machine learning applications according to requirements.
  • Provide support to achieve successfully deployed models at conclusion of projects.
  • Plan and manage data analysis workflows.
  • Create charts, graphs, maps, and data visualization tools to provide an accessible way to see/understand trends, patterns, outliers, in data.
  • Select appropriate datasets and data representation methods.
  • Run machine learning tests and experiments.
  • Train and retrain systems when necessary.
  • Extend existing ML libraries and frameworks.

We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.