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Senior Machine Learning Engineer Jobs in Alberta

Senior Software Engineer - Canada

Calgary, AB ยท Remote

CA$120K - CA$150K/yr

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... As platform engineers, we are building a next-generation machine learning platform, which ...

Description The Opportunity We are looking for a proactive, growth-minded Senior Data Analyst / ML ... GCP Professional Machine Learning Engineer Certification * Working knowledge of leveraging Claude ...

Description The Opportunity We are looking for a proactive, growth-minded Senior Data Analyst / ML ... GCP Professional Machine Learning Engineer Certification * Working knowledge of leveraging Claude ...

Senior ML Platform Engineer

Calgary, AB ยท On-site

CA$182K - CA$209K/yr

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

The RoleThe Spatial AI Engineer builds the systems that let AI models, applications, and ... You will design and implement machine learning systems that operate directly on spatial datasets ...

The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models. Key Responsibilities: * Build ML deployment ...

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 ...

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Showing results 1-20

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 24, 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 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 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 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:

Machine Learning Resident - Client: Zamplo (8 month term)

Alberta Machine Intelligence Institute

Edmonton, AB โ€ข On-site

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

"Join us for a unique ML Resident role focusing on improving patient outcomes by predicting risk of an adverse event using ML/DL. You'll work in a fast-paced and dynamic team of machine learning scientists, healthcare providers, and domain experts ." - Soumik Farhan, Machine Learning ScientistAbout AmiiOne of Canada's three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world's top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.About the RoleThis is a paid residency that will be undertaken over a eight-month period with the potential to be hired by our client afterwards.

The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities. About our ClientZamplo is a digital health company transforming the way individuals, clinicians, and researchers engage with health data. Its connected health platform empowers people to track and share their own health information, while providing real-time insights that support better care and outcomes.

Zamplo develops innovative, patient-centered tools that reduce costs and improve collaboration across the healthcare system.The Zamplo platform offers two complementary products:Zamplo App: Allows patients to track symptoms, medications, routines, and share information with their care team. It helps patients better manage their health and prepare for meaningful conversations with providers.Zamplo Research: An electronic data capture platform designed for researchers, clinicians, and organizations. With patient consent it enables collection of patient-reported outcomes and wearable data, supports electronic consent, and streamlines data management to advance clinical research and improve care delivery.About the Project The project aims to use machine learning to classify a patient's risk of an adverse event leading to an emergency room visit following radiation therapy.

This risk assessment will use socio-demographic, non-medical and medical data. By identifying patients with a higher risk of an adverse event earlier, patients, healthcare providers, caregivers, and community stakeholders can implement proactive measures to improve patient outcomes.As research in this specific area is limited, the resident would approach the classification problem in a number of ways, each with its own set of experiments and models to determine the best option to implement. Following model development, the results will be externally validated in both retrospective and prospective manners.Required Skills / ExpertiseWe're looking for a talented and enthusiastic individual with solid knowledge of machine learning, experience working with health care data, and a passion to improve individual health outcomes.Key Responsibilities: Utilize a range of supervised, unsupervised methods to build a robust and deployable predictive model.

Ingest and understand (including performing exploratory data analysis and baseline statistical assessments) medical data from multiple patient health data sources. Experiment and fine-tune the model(s) as necessary based on the performance of baseline and deployment expectations. Collaborate with the project team and domain experts to iteratively develop models and define identified health event outcomes.

Implement model explainability and interpretability techniques to provide insights to patients and clinicians. Participate in regular meetings with the client and stakeholders, preparing presentations and reports. Research and implement different approaches to the problem from literature as well as publicly available tools.

Required Qualifications: Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in predictive health or medical applications. Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.

Proficient in Python programming language and related ML frameworks, libraries and toolkits. Solid understanding of classical statistics and its application in model validation. Familiarity with Linux, Git version control, and writing clean code.

A positive attitude towards learning and understanding a new applied domain . Must be a Permanent Resident or Canadian Citizen Preferred Qualifications: Familiarity with and hands-on experience with medical and/or health data. Experience with survival analysis and time-to-event modeling.

Publication record in peer-reviewed academic conferences or relevant journals in machine learning. Experience/familiarity with software engineering best practices. Experience using cloud platforms (GCP, AWS, Azure, etc.) Experience in using statistical tools such as SPSS, Stata etc.

Non-Technical Requirements: Desire to take ownership of a problem and demonstrate leadership skills. Interdisciplinary team player enthusiastic about working together to achieve excellence. Capable of critical and independent thought.

Able to communicate technical concepts clearly and advise on the application of machine intelligence. Intellectual curiosity and the desire to learn new things, techniques, and technologies. Why You Should ApplyBesides gaining industry experience, additional perks include: Work under the mentorship of an Amii Scientist for the duration of the project.

Participate in professional development activities. Gain access to the Amii community and events. Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer).

Build your professional network. The opportunity for an ongoing machine learning role at the client's organization at the end of the term (at the client's discretion). Location: Alberta PreferredHow to ApplyIf this sounds like the opportunity you've been waiting for, please don't wait for the closing April 24, 2026 to apply - we're excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes!

When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.Applicants must be legally eligible to work in Canada at the time of application.Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability.

Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won't be used in the selection process.