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Machine Learning Engineer Jobs in Alberta (NOW HIRING)

YO AI Labs

Mental Health Expert - Remote

Edmonton, AB · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

YO AI Labs

Mental Health Expert - Remote

Calgary, AB · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

Royal Bank of Canada

Principal AI Engineer

Calgary, AB · On-site

... in machine learning, has access to rich and massive datasets, and offers the computational ... Apply rigorous engineering practices, including code quality, automated testing, CI/CD, performance ...

HUB

Data Scientist

Edmonton, AB · On-site

The successful candidate brings classical data science fundamentals (statistics, machine learning, experimental design) and is equally comfortable in the emerging world of AI engineering: prompting ...

HUB

Data Scientist

Red Deer, AB · On-site

The successful candidate brings classical data science fundamentals (statistics, machine learning, experimental design) and is equally comfortable in the emerging world of AI engineering: prompting ...

Drilling Info

Senior Data Engineer - 26206

Calgary, AB · On-site +1

The Team: We're looking for a Senior Data Engineer to lead the technical implementation of our next ... Experience supporting forecasting, optimization, machine learning, or analytical systems. * Cloud ...

Enverus

Senior Data Engineer - 26206

Calgary, AB · On-site

The Team: We're looking for a Senior Data Engineer to lead the technical implementation of our next ... Experience supporting forecasting, optimization, machine learning, or analytical systems. * Cloud ...

Stream Systems Ltd.

Systems Developer

Calgary, AB · Hybrid

Systems Developer Company Overview Stream Systems (www.streamsystems.ca) is a leading-edge ... Our SimOpti intelligence platform brings AI, machine learning and simulation to power business ...

Katalyst Data Management

AI/ML Engineer

Calgary, AB · On-site

KDM is seeking an AI/ML Engineer to support the operation, optimization, and reliability of the ... Monitor, maintain, and optimize machine learning infrastructure, including test environments and ...

New

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 ...

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Showing results 41-60

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 Sep 10, 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 is a machine learning engineer?

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 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 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 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.

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
Infographic showing various Machine Learning Engineer job openings in Alberta as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 69% Full Time, 28% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $142,956 per year, or $68.7 per hour.

Mental Health Expert - Remote

Edmonton, AB • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$200 - $350/hr

Full-time

Posted 14 days ago

Job description

AI/ML Engineer

Job Type: Full-Time
Location: Remote

Job Summary

We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure. You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications.

Key Responsibilities
  • Design, implement, and optimize AI/ML solutions using LLMs, RAG, and prompt engineering.
  • Develop and orchestrate multi-agent systems using LangGraph and LangChain.
  • Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
  • Build robust ETL and data pipelines, metadata catalogs, and ontologies for AI training and inference.
  • Develop and maintain REST APIs and SDK integrations.
  • Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.
  • Follow modern secure coding, DevOps, and CI/CD practices.
  • Document technical decisions and communicate complex concepts effectively to technical and non-technical stakeholders.
Required Skills & Qualifications
  • Strong Python proficiency for AI/ML development, including REST APIs and SDK integrations.
  • Hands-on production experience with LLMs, RAG, and prompt engineering.
  • Experience with multi-agent orchestration, tool use, LangGraph, and LangChain.
  • Strong knowledge of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
  • Experience building data pipelines, ETL processes, metadata catalogs, and ontologies.
  • Strong understanding of secure coding and CI/CD practices.
  • Excellent written and verbal communication skills.
Preferred Qualifications
  • Experience with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
  • Knowledge of MCP, metadata catalog platforms, and advanced API development.
  • Experience working in government, regulated, or security-sensitive cloud environments.
  • Familiarity with relevant compliance and security standards.