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Machine Learning Engineer Jobs in Alberta (NOW HIRING)

DataVisor

Delivery Engineer - Canada

Calgary, AB

CA$80K - CA$120K/yr

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... Position Overview: We are seeking a Delivery Engineer to join our Delivery team. The ideal ...

Clio

ML Platform Engineer

Calgary, AB · On-site

CA$152K - CA$174K/yr

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

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

AppDirect

Software Developer

Calgary, AB

Exposure to machine learning model integration or building AI-powered product features is an asset ... engineering roles where asking the right questions shapes outcomes. At AppDirect, we believe that ...

PwC

AI & Advanced Analytics, Senior Manager

Calgary, AB

CA$168K - CA$218K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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 ...

TELUS

Data Scientist

Edmonton, AB

Data Architecture & Engineering: Design and build robust data pipelines and architectures on Google ... Conduct in-depth exploratory data analysis and apply statistical methods, machine learning ...

TELUS

Data Scientist

Calgary, AB

Data Architecture & Engineering: Design and build robust data pipelines and architectures on Google ... Conduct in-depth exploratory data analysis and apply statistical methods, machine learning ...

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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 Jul 22, 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $142,956 per year, or $68.7 per hour.
Delivery Engineer - Canada

Delivery Engineer - Canada

DataVisor

Calgary, AB

CA$80K - CA$120K/yr

Full-time

Medical, PTO

Posted 19 days ago

Job description

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are seeking a Delivery Engineer to join our Delivery team. The ideal candidate will lead client communications and drive end-to-end project delivery, while designing and implementing innovative integration solutions that meet both technical and business requirements.This role requires close collaboration with clients, sales teams, and internal stakeholders to ensure successful project outcomes. As a technical delivery leader, the TPM will own and manage all engineering work streams, coordinating across teams to keep projects on schedule and aligned with scope. The role is hands-on, requiring the ability to contribute directly to technical implementation and problem-solving as needed.

Key Responsibilities:

  • Manage and drive client communications throughout the entire project delivery, align different client stakeholders, ensure project is delivered successfully without delay.
  • Work closely with clients, sales teams, and other stakeholders to ensure successful project outcomes.
  • Understand the client's product and business logic to recommend the best solution that addresses specific client needs. Provide strong solution and consulting services.
  • Take the project management role to ensure the client onboarding project runs as expected and under control.
  • Provide technical expertise and guidance throughout the implementation and deployment phases, to integrate with the client systems.
  • Work closely with product and engineering teams to ensure seamless integration of new features and technologies into existing systems.
  • Stay updated on financial services industry trends and emerging technologies to continuously improve our solutions and offerings.
  • Conduct presentations and demonstrations of proposed solutions to clients and stakeholders.

Requirements

Qualifications:

  • Bachelor's degree in Computer Science, Engineering or a related field is required; a Master's degree in a business-related discipline (e.g., MBA, MIS, Information Systems, Management, or Analytics) is preferred.
  • Basic understanding of software development, system architecture, and system integration concepts; exposure to SaaS platform data integration is a plus.
  • Strong verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Enjoys working with clients and stakeholders, with a service-oriented mindset and interest in client-facing responsibilities.
  • Ability to work collaboratively in a team environment and support multiple projects under guidance and supervision.
  • Demonstrates strong problem-solving skills, attention to detail, and a willingness to learn in a fast-paced environment.
  • Familiarity with anti-fraud concepts in the financial services or internet industry is a plus.
  • Exposure to real-time computing, big data technologies, or machine learning through coursework, internships, or project experience is a plus.

Benefits

1. Health Insurance, PTO, stock option

2. The expected salary range for this role is CAD $80,000 - $120,000 per year, depending on experience, qualifications, and location. Final compensation will be determined based on job-related skills and business needs

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