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Machine Learning Engineer Jobs in Alberta (NOW HIRING)

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 ...

New

... engineering, cloud computing, artificial intelligence, and machine learning. If you are excited about the prospect of using cutting-edge technology to drive sales and revenue growth, then we ...

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 ...

MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to ...

Exposure to integrating machine learning, generative AI, or LLM-based components into application features * Experience mentoring less experienced engineers Energy industry experience is not required ...

Exposure to integrating machine learning, generative AI, or LLM-based components into application features * Experience mentoring less experienced engineers Energy industry experience is not required ...

... 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 ...

... generation of AI engineers, and transform finance operations. Join our team and what we'll ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

... generation of AI engineers, and transform finance operations. Join our team and what we'll ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

Intermediate Spatial Ecologist

Calgary, AB ยท On-site +1

CA$43.90 - CA$60.40/hr

Develop and apply machine learning, AI, and advanced analytical approaches to ecological modeling ... Strong programming skills in Python for data analysis, automation, and visualization.

Intermediate Spatial Ecologist

Calgary, AB ยท On-site +1

CA$43.90 - CA$60.40/hr

Develop and apply machine learning, AI, and advanced analytical approaches to ecological modeling ... Strong programming skills in Python for data analysis, automation, and visualization.

Showing results 41-60

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 Aug 13, 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 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 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 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:
Infographic showing various Machine Learning Engineer job openings in Alberta as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $142,956 per year, or $68.7 per hour.

Data Scientist

HUB

Edmonton, AB โ€ข On-site

Full-time

Retirement

Posted 2 days ago

New


Job description

Hi, we're HUB!

We are a leading North American insurance brokerage that advises businesses and individuals on how to reach their goals. When you partner with us, you're at the center of a vast network of risk, insurance, employee benefits, retirement and wealth management specialists that bring clarity to a changing world with tailored solutions and unrelenting advocacy - so you're ready for tomorrow.

The Opportunity!

This is a permanent, full-time position, reporting to the Director, Business Intelligence at HUB Canada West (HCW).

As the Data Scientist, you are the technical engine of a small, high-leverage analytics function. This role exists to turn HCW's growing data foundation across cloud data platforms and SQL into measurable business value: predictive models, self-serve analytics, intelligent automation, and AI-powered tools that change how branches and leadership make decisions.

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 and orchestrating large language models, building reusable AI workflows, and integrating LLMs into BI products. As the discipline of data science continues to converge with AI engineering, we want someone who can move fluidly across both.

You will operate as a senior individual contributor and a generalist problem solver. You enjoy ambiguity, you pick up new tools quickly, and you care about outcomes more than orthodoxy.

What You'll Bring to Our Team -

  • 5+ years of hands-on experience in data science, analytics engineering, advanced analytics, or a directly related applied technical role.

  • Bachelor's or Master's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Data Science, Engineering, or similar). Equivalent demonstrated experience will be considered in lieu of formal credentials.

  • Background in insurance, financial services, or another regulated industry is a strong asset, with practical familiarity with concepts such as policies in force, premium, retention, and producer compensation.

  • A generalist, problem-solving mindset: comfortable picking up new tools, languages, and platforms; energized by ambiguity rather than blocked by it.

Skills & Competencies:

Must-Haves

  • Strong SQL skills, including comfort with complex joins, and query optimization against large datasets.

  • Strong Python skills for analysis, modelling, and automation (pandas, scikit-learn, NumPy), plus practical experience with ML Algorithms such as Random Forest, Recommender Systems or Clustering.

  • Demonstrated production experience with Power BI, including data modelling, DAX, and the ability to design dashboards that leadership can intuitively use.

  • Working knowledge of statistics, machine learning fundamentals, and model evaluation; able to choose the right tool for the question rather than reaching for the most complex one.

  • Demonstrated ability to use Claude (or other AI tools like ChatGPT, Copilot, or equivalent) as a serious working tool: structured prompting, iterative refinement, awareness of failure modes, guardrails, and the discipline to verify outputs.

  • Excellent written and verbal communication, with the ability to translate technical findings into business decisions and to write clearly for executive audiences.

Nice-to-Haves

  • Experience building Claude Skills, artifacts, MCP server integrations, or agentic AI workflows.

  • General familiarity with Google Cloud Platform, particularly BigQuery, is a plus as HCW's data environment evolves.

  • Experience with light data engineering tooling such as dbt, Airflow, or Cloud Composer.

  • Comfort with version control (Git), code review practices, and collaborative development workflows.

  • Familiarity with Canadian data privacy requirements (PIPEDA) and the practical realities of working with sensitive customer and HR data.

A Day in the Life -

Analytics and Modelling:

  • Design and deliver applied analytics and machine learning solutions across sales, retention, finance, operations, and talent (for example, customer segmentation, churn and renewal probability, book of business analytics, producer performance modelling).

  • Translate ambiguous business questions from leadership into structured analytical problems, choose the right level of methodological rigour for the decision at hand, and communicate results in plain language.

  • Apply solid statistical thinking to model evaluation, uncertainty quantification, and the honest framing of data quality limitations.

AI Engineering:

  • Build and maintain production-grade prompts, Claude Skills, and AI-assisted workflows that extend HCW's analytical reach (for example, manager-facing prompt playbooks for self-serve call analytics).

  • Integrate large language models with HCW data sources to enable natural-language analytics, automated narrative generation, and intelligent document processing.

  • Stay current with the rapidly evolving AI tooling landscape and bring promising techniques into HCW thoughtfully, with appropriate guardrails.

Data Access and Transformation:

  • Extract, join, and transform data from HCW's data warehouse, Power BI semantic layer, and other source systems to support analytical work. Note: this is not a heavy data engineering role. Platform, ingestion, and core pipeline work sits primarily with the Canada Data team and Corporate IT. The Data Scientist is expected to access and shape data, not to build the warehouse.

  • Engineer features, build reproducible analytical pipelines, and document data lineage and assumptions.

Business Intelligence and Self-Serve:

  • Build interactive Power BI dashboards that make analytical output usable by branch managers, regional leadership, and corporate executives.

  • Develop reusable Power BI templates and data structures that let branch managers, regional leadership, and corporate executives self-serve their own analysis without relying on ad hoc analyst support.

  • Track adoption of Power BI reports and dashboards, and surface how they are being used to drive measurable business value across branches and leadership.

Automation:

  • Identify high-friction manual reporting and operational workflows, then automate them using Python, scheduled data pipeline jobs, Power Automate, or AI-powered workflows.

  • Design automation that is observable, recoverable, and trusted by the business.

Stakeholder Engagement and Communication:

  • Work directly with the COO, regional leadership, and operational managers to scope work and present findings.

  • Coach and uplift the broader BI community of practice on Python, SQL, AI tooling, and analytical thinking.

  • Collaborate with the Canada Data team and Corporate IT on data standards, governance, and shared platform decisions.

Salary Expectations -

The expected salary range for this position is $90,000.00 to $115,000.00 and will be impacted by factors such as the successful candidate's skills, experience and working location, as well as the specific position's business line, scope, and level. HUB International is proud to offer comprehensive benefit and total compensation packages which could include extended health benefits, disability insurance, RRSP matching, paid-time-off benefits, and eligible bonuses. If you believe that your qualifications and experience surpass the minimum requirements for this role, we encourage you to submit your application. By doing so, we will be able to keep your application on file for consideration for potential future positions within our organization.

Why Join HUB?

  • Do you enjoy making friends? We love making friends; join our team of amazing people who all get along and thrive together!

  • We work hard and play hard! Get ready for our Staff Holiday Parties!!

  • Paid day off for your birthday - we want to celebrate you!

  • Paid day off for volunteering in your community - HUB is a company that gives back and is active in our communities.

  • Room to grow within the organization.

  • Lots of company perks, benefits, RRSP matching and great compensation.

Your Future with HUB -

Choose a career with HUB International and take the first step toward creating a future that combines a diverse, challenging work environment with financial security and career satisfaction. By joining HUB, you will become part of a rapidly growing company that offers significant opportunity for advancement.

At HUB, we value education and continuous learning, and we will assist you along your career development path. We provide HUB Ready training for new employees, as well as financial support for licensing, industry designations, management & leadership development, and other related courses, designations or programs.

What makes us different than all the rest?

Our Vision: To be everywhere risk exists - today and tomorrow. Helping protect what matters most.

Our Mission: To protect and support the aspirations of individuals, families and businesses. To empower our employees to learn, grow and make a difference in their communities.

Our Core Values:

  • Entrepreneurship: We encourage innovation and educated risk-taking.

  • Integrity: We do the right thing every time.

  • Teamwork: We work together to maximize results.

  • Accountability: We measure and take responsibility for outcomes.

  • Service: We serve customers, communities and colleagues.

If you value what we value, and like the perks along the way - Apply TODAY!

The employment offer is contingent upon completion of a successful background check.

HUB is a company where your contributions will make a difference. We invite you to learn more about our team at www.hubinternational.com. If you require any accommodations during the hiring process, please reach out to hcw.hr@hubinternational.com to request this. Only candidates selected for an interview will be contacted.

#LI-POST

#LI-onsite

Department Business OperationsRequired Experience: 5-7 years of relevant experienceRequired Travel: No Travel Required

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