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Senior Machine Learning Engineer Jobs in Alberta

Data Elephant Inc

Senior AI / ML Engineer

Calgary, AB · On-site

We are looking for a Senior AI/ML Engineers to join our team, that sit at the intersection of ... Implement and operationalize machine learning models (training, deployment, monitoring) * Work with ...

WCB Alberta

Data Scientist

Edmonton, AB · Hybrid

CA$85.18K - CA$113.65K/yr

Proficiency in a machine learning programming language (Python) is mandatory. * Strong SQL skills are a fundamental requirement. * Extensive experience in data preparation techniques, including data ...

WCB Alberta

Data Scientist

Calgary, AB · Hybrid

CA$85.18K - CA$113.65K/yr

Proficiency in a machine learning programming language (Python) is mandatory. * Strong SQL skills are a fundamental requirement. * Extensive experience in data preparation techniques, including data ...

Kyndryl

Senior Data & AI Consultant

Calgary, AB

The Role We are seeking a Senior Data & AI Consultant to lead data and AI transformation programs ... Oversee delivery of end-to-end engagements spanning data engineering, machine learning, generative ...

TELUS

L4 Technical Professional

Calgary, AB

You will work closely with a team of data scientists and data engineers to deploy solutions and drive innovation using machine learning and NLP techniques. The ideal candidate has a deep ...

TELUS

L4 Technical Professional

Edmonton, AB · On-site

You will work closely with a team of data scientists and data engineers to deploy solutions and drive innovation using machine learning and NLP techniques. The ideal candidate has a deep ...

Pulse Medica

Senior Software Developer

Edmonton, AB

Sr. Software Developer PulseMedica is seeking a Senior Software Developer to help build the next ... Experience with machine learning. * Experience with 3D Rendering. * Experience with embedded SW ...

Pulse Medica

Senior Software Developer

Edmonton, AB · On-site

Salary: Sr. Software Developer PulseMedica is seeking a Senior Software Developer to help build the ... Experience with machine learning. * Experience with 3D Rendering. * Experience with embedded SW ...

Royal Bank of Canada

Staff AI/ML Engineer

Calgary, AB · On-site +1

Staff AI/ML Engineer What's the opportunity? We're looking for a seasoned Staff AI/ML Engineer to ... In this role you will own the end-to-end lifecycle of machine learning systems-from experimentation ...

Halliburton

AI/ML work experience and machine Learning technologies (Python, TensorFlow etc.) * Experience in ... be available including Senior Geostatistican/Developer. Halliburton is an Equal Opportunity ...

Hubbell Incorporated

Sr Research Engineer

Edmonton, AB · On-site

Research activities span sensors, controls, communications, analytics (including machine learning ... The Sr. Research Engineer will contribute to the research, development, implementation, and ...

Olsen Consulting

Senior Data Analyst

Calgary, AB · On-site +1

Senior Data Analyst Olsen Consulting specializes in the implementation and optimization of ... and Machine Learning algorithms in a business context - Academic rigor with a propensity for ...

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Senior Machine Learning Engineer information

See Alberta salary details

$45K

$165.3K

$248.5K

How much do senior machine learning engineer jobs pay per year?

As of Jun 1, 2026, the average yearly pay for senior machine learning engineer in Alberta is $165,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,500.00 and $184,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

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 Senior Machine Learning Engineer jobs in Alberta? For Senior Machine Learning Engineer jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Alberta look for? The top searched job categories for Senior Machine Learning Engineer jobs in Alberta are:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Alberta as of May 2026, with employment types broken down into 1% Internship, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 78% Physical, 8% Hybrid, and 14% Remote job distribution, with an average salary of $165,321 per year, or $79.5 per hour.

Senior AI / ML Engineer

Data Elephant Inc

Calgary, AB • On-site

Full-time

Posted 11 days ago

Job description

We are looking for a Senior AI/ML Engineers to join our team, that sit at the intersection of software engineering, data engineering, and applied AI.


This role is ideal for someone who enjoys building end-to-end solutions - from data pipelines and backend systems to AI-powered applications - and wants to work on real-world industrial use cases.


You will play a key role in designing and delivering modern AI-enabled solutions that help our clients transform legacy workflows into intelligent, scalable systems.


In this position, you'll contribute to a variety of impactful client projects, including:


  • Building AI-powered anomaly detection systems for operational and industrial data
  • Modernizing asset management workflows
  • Developing natural language interfaces for querying enterprise and operational data
  • Designing and implementing AI agents and copilots for business users
  • Creating scalable data pipelines and ML workflows in cloud environments
  • Enabling real-time and batch data processing for analytics and AI use cases


Responsibilities:


  • Design, build, and deploy end-to-end AI/ML solutions in production environments
  • Develop robust backend systems and APIs to support AI-driven applications
  • Build and maintain data pipelines and feature engineering workflows
  • Implement and operationalize machine learning models (training, deployment, monitoring)
  • Work with modern AI tooling (LLMs, agents, orchestration frameworks)
  • Collaborate with clients to translate business problems into technical solutions
  • Contribute to architecture decisions and best practices across projects
  • Mentor client team members and contribute to internal capability building


Required Skills & Experience


  • 5+ years of experience in software engineering, data engineering, or ML engineering
  • Strong programming and querying skills (Python, SQL, PySpark)
  • Experience building production-grade systems (APIs, microservices, pipelines)
  • Hands-on experience with AI/ML workflows and model deployment
  • Familiarity with modern AI/GenAI tooling and concepts
  • Experience with cloud platforms (Azure, AWS, Databricks)
  • Strong understanding of data engineering concepts (ETL, data modeling, pipelines)
  • Strong familiarity with the Databricks ecosystem (including AgentBricks, Genie - Databricks certifications strongy preferred)
  • Experience with LLM frameworks and agent-based architectures
  • Modern developer tooling (Cursor, AI-assisted development, "vibe coding")
  • Experience working with industrial, utilities, or energy sector data


This role presents an exciting opportunity to work on practical, high-impact AI use cases - not just prototypes, shape how AI is applied to client environments, and change the game on traditional processes and platforms.Come join a growing organization helping clients take a new, lean and value-driven approach to data and engineering!

Apply