ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in Alberta (NOW HIRING)

Viridien

Machine Learning Engineer

Calgary, AB

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 ...

Hays

Machine Learning Engineer

Calgary, AB · Hybrid

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 ...

New

Takeaway

Machine Learning Engineer

Edmonton, AB · Remote

As a Machine Learning Engineer, you will be part of the Data Science team inside the Product and Tech group with +2200 brilliant developers, engineers, analysts and researchers. Honestly, it is a ...

Takeaway

Senior Machine Learning Engineer

Edmonton, AB · On-site

As a Senior ML Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement.

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Alberta

Machine Learning Engineer information

See Alberta salary details

$64.5K

$143K

$218.5K

How much do machine learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer in Alberta is $142,956.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $166,000.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Alberta? The most popular types of Machine Learning Engineer jobs in Alberta are:
What are popular job titles related to Machine Learning Engineer jobs in Alberta? For Machine Learning Engineer jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Alberta look for? The top searched job categories for Machine Learning Engineer jobs in Alberta are:
What are popular job titles related to Machine Learning Engineer jobs in AB? For Machine Learning Engineer jobs in AB, the most frequently searched job titles are:
Machine Learning Engineer jobs near you

Machine Learning Engineer

Viridien

Calgary, AB

Full-time

Posted 5 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.

Apply