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Machine Learning Engineer Jobs in Alberta (NOW HIRING)

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

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

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

... 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 ...

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 ...

Apply Early

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 ...

Apply Early

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 ...

Apply Early

MLOps Developer III

Calgary, AB · On-site +1

CA$10/hr

Terra Sense Analytics is looking for a MLOps Developer We truly believe that it's our team that ... of machine learning algorithms. * Serve as a technical reference point, coaching staff and ...

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 ...

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 ...

... 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 ...

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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 ...

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Showing results 1-20

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 2, 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.

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:
Infographic showing various Machine Learning Engineer job openings in Alberta as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 3% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $142,956 per year, or $68.7 per hour.

Senior ML Platform Engineer

Clio

Calgary, AB

CA$182K - CA$209K/yr

Full-time

Medical, Dental, Vision

Posted 28 days ago


Job description

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely.

We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.

Summary:

We are currently seeking a Senior ML Platform Engineer to join our Engineering team. This role is available to candidates across Canada. If you are local to our Toronto, Calgary, or Burnaby hubs, then you will be expected to be in office minimum two days per week for our Anchor Days.

What your team does:

Our ML Platform team builds and operates the scalable infrastructure and robust platforms that power AI solutions across Clio. We blend deep AI and ML expertise with strong software engineering and cloud infrastructure skills to enable the entire lifecycle of machine learning and generative AI - spanning experimentation, deployment, monitoring, and continuous improvement. By applying best practices in CI/CD, observability, cost optimization, and model governance, and leveraging state-of-the-art tools and frameworks, we ensure our AI systems are reliable, performant, and aligned with business goals. We partner closely with ML engineers, data engineers, and product teams to accelerate the delivery of impactful AI capabilities.

What a day in the life might look like:
  • Build and deploy LLM-based solutions that help Clio's customers save time and improve operational efficiency

  • Collaborate cross-functionally with engineering, product management, operations, and data science to identify and develop new ML-driven features

  • Evaluate and integrate new ML tools and frameworks to accelerate experimentation and optimize operations

  • Troubleshoot and resolve production issues such as data drift and model latency using observability tools and logs

  • Participate in design reviews and contribute to architectural decisions shaping Clio's AI platforms

  • Engage in code reviews within your team and across the company, providing and receiving constructive feedback to maintain high standards

  • Continuously learn, challenge yourself, and grow as a machine learning expert while mentoring and collaborating with teammates

What you may have:
  • Solid Python or Ruby on Rails development skills, with experience building production-grade applications, services, or ML tooling

  • Expertise in cloud infrastructure (AWS, GCP, or Azure), including Kubernetes, and infrastructure-as-code (Terraform, Helm, or similar)

  • Experience with CI/CD and automating model training, testing, and deployment pipelines

  • Understanding of machine learning and AI concepts, workflows, and lifecycle management

  • Demonstrated leadership skills, with the ability to mentor and guide team members effectively

  • Ability to fully own the design and delivery of robust, scalable solutions from concept through implementation

  • You excel at breaking down complex, challenging problems into manageable parts and iterating toward effective solutions

  • You are naturally curious and love to dig deep into problems, constantly asking, "why?"

  • You communicate clearly and concisely, regardless of the medium (text, voice, or in-person)

  • You value collaboration and proactively seek to build context to power your decisions

  • You have a team-first mentality and will naturally support co-workers when you sense they are facing difficulty

  • Demonstrate a keen interest in improving your craft by using AI

Serious bonus points if you have:
  • Familiarity with AI observability tools (logging, metrics, tracing) to monitor and debug AI systems

  • Awareness of ML governance, responsible AI, and best practices for secure, compliant AI operations

  • Proficient in developing and utilizing guardrails to ensure secure, reliable, and compliant AI operations

This is for a new role.

    What you will find here:

    Compensation is one of the main components of Clio's Total Rewards Program. We have developed a series of programs and processes to ensure we are creating fair and competitive pay practices that form the foundation of our human and high-performing culture.

    Some highlights of our Total Rewards program include:

    • Competitive, equitable salary with top-tier health benefits, dental, and vision insurance

    • Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.

    • Flexible time off policy, with an encouraged 20 days off per year.

    • $2000 annual counseling benefit

    • RRSP matching and RESP contribution

    • Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

    The expected salary range* for this role is $154,700 to $182,000 to $209,300 CAD. There are a separate set of salary bands for other regions based on local currency.


    *Our salary bands are designed to reflect the range of skills and experience needed for the position and to allow room for growth at Clio. For experienced individuals, we typically hire at or around the midpoint of the band. The top portion of the salary band is reserved for employees who demonstrate sustained high performance and impact at Clio. Those who are new to the role may join below the midpoint and develop their skills over time. The final offer amount for this role will be dependent on geographical region, applicable experience, and skillset of the candidate.

    Diversity, Inclusion, Belonging and Equity (DIBE) & Accessibility

    Our team shows up as their authentic selves, and are united by our mission. We are dedicated todiversity, equity and inclusion. We pride ourselves in building and fostering an environment where our teams feel included, valued, and enabled to do the best work of their careers, wherever they choose to log in from. We believe that different perspectives, skills, backgrounds, and experiences result in higher-performing teams and better innovation. We are committed to equal employment and we encourage candidates from all backgrounds to apply.

    Clio provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.

    Learn more about our culture atclio.com/careers

    We're a Human and High Performing AI company, meaning we use artificial intelligence to improve all of our operations. In recruitment, AI helps us streamline the process for greater efficiency. However, we've built our systems to ensure that a human always reviews AI-generated output, and we never make automated hiring decisions.

    Disclaimer: We only communicate with candidates through official @clio.com email addresses.