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Machine Learning Engineer Jobs in Alberta (NOW HIRING)

Clio

Senior ML Platform Engineer

Calgary, AB · On-site

CA$182K - CA$209K/yr

We are currently seeking a Senior ML Platform Engineer to join our Engineering team. This role is ... Understanding of machine learning and AI concepts, workflows, and lifecycle management

New

C-Serv

AI Offensive Security Engineer

Calgary, AB · On-site

This role sits at the intersection of adversarial machine learning, enterprise security ... Partner closely with engineering, security, and compliance functions * Present findings clearly to ...

New

TELUS

Senior Data Analyst (L4)

Edmonton, AB

GCP Professional Machine Learning Engineer Certification * Working knowledge of leveraging Claude in the workflows * Experience with Google Vertex AI or Kubeflow for ML orchestration * Background in ...

TELUS

Senior Data Analyst (L4)

Calgary, AB

GCP Professional Machine Learning Engineer Certification * Working knowledge of leveraging Claude in the workflows * Experience with Google Vertex AI or Kubeflow for ML orchestration * Background in ...

Royal Bank of Canada

Staff AI Engineer

Calgary, AB · On-site

... and machine learning, has access to rich and massive datasets, and offers the computational ... Collaborating with engineers and AI researchers to architect, build, integrate and deploy AI ...

TELUS

Staff Applied AI/ML Scientist

Edmonton, AB

Expertise in machine learning frameworks such as TensorFlow, Pytorch, and Keras * Strong understanding of software and AI development lifecycles, with experience in DevOps and MLOps practices

TELUS

Staff Applied AI/ML Scientist

Calgary, AB

Expertise in machine learning frameworks such as TensorFlow, Pytorch, and Keras * Strong understanding of software and AI development lifecycles, with experience in DevOps and MLOps practices

Miratech

Google DialogFlow Engineer (Python)

Calgary, AB · On-site +1

Leverage natural language processing (NLP), LLM, and machine learning (ML) techniques, including ... Experience with programming languages such as JavaScript, Python, or Node.js. * Familiarity with ...

Data Elephant Inc

Senior AI / ML Engineer

Calgary, AB · On-site

Implement and operationalize machine learning models (training, deployment, monitoring) * Work with ... Strong programming and querying skills (Python, SQL, PySpark) * Experience building production ...

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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 5, 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

MLOps Engineer (Energy) - MLEEAS

NavitasPartners

Leduc, AB

CA$30/hr

Full-time

Posted yesterday

Job description

Job Title : MLOps Engineer (Energy)Industry

Energy & Utilities

Position Overview

The MLOps Engineer will establish and manage scalable ML infrastructure, ensuring efficient deployment, monitoring, governance, and lifecycle management of machine learning solutions.

Responsibilities
  • Build ML deployment pipelines.
  • Implement CI/CD for ML systems.
  • Automate model retraining workflows.
  • Monitor model performance and drift.
  • Manage ML infrastructure and environments.
  • Ensure governance and compliance requirements.
Required Skills
  • MLOps
  • Kubernetes
  • Docker
  • MLflow
  • Databricks
  • Azure ML / SageMaker / Vertex AI
  • GitHub Actions
  • Terraform
Preferred Skills
  • Energy Forecasting Models
  • Asset Optimization Models
  • Real-Time Monitoring Systems
Mandatory Experience
  • 5+ years in MLOps or ML Platform Engineering.
  • Must have prior Energy industry experience.


For more details reach at resumes@navitassols.com