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Machine Learning Intern Jobs in Alberta (NOW HIRING)

Machine Learning Intern information

See Alberta salary details

$9

$47

$88

How much do machine learning intern jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for machine learning intern in Alberta is $47.13, according to ZipRecruiter salary data. Most workers in this role earn between $38.46 and $52.64 per hour, depending on experience, location, and employer.

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

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What does a Machine Learning Intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What types of projects do Machine Learning Interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What Does a Machine Learning Intern Do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

What are the most commonly searched types of Machine Learning jobs in Alberta? The most popular types of Machine Learning jobs in Alberta are:
What are popular job titles related to Machine Learning Intern jobs in Alberta? For Machine Learning Intern jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern jobs in Alberta look for? The top searched job categories for Machine Learning Intern jobs in Alberta are:
What cities in Alberta are hiring for Machine Learning Intern jobs? Cities in Alberta with the most Machine Learning Intern job openings:
Infographic showing various Machine Learning Intern job openings in Alberta as of July 2026, with employment types broken down into 10% Internship, 1% As Needed, 55% Full Time, 31% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $98,034 per year, or $47.1 per hour.

Machine Learning Resident - Client: HQA (12 month term)

Alberta Machine Intelligence Institute

Calgary, AB

Full-time

Posted 10 days ago


Job description

"If you are looking to develop a text-to-SQL engine using LLMs that can benefit from RAG-based semantics, self-correcting agentic AI loops and domain fine tuning for the healthcare sector, this is a great opportunity. Join a team of ML scientists and domain experts to build AI solutions in practice." - Anjana Puliyanda, Machine Learning ScientistAbout the RoleThis is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client, Health Quality Alberta, afterwards (note: at the discretion of the client). The Resident will report to an Amii Scientist and regularly consult with the client team to share insights and engage in knowledge transfer activities. Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development. This is a rare opportunity to be mentored by world-class scientists and to develop something truly impactful. About our ClientHealth Quality Alberta is a provincial agency that brings together patients, families, and their partners from across healthcare and academia to inspire improvement in patient safety, person-centred care, and health service quality. They assess and study the healthcare system, identify effective practices, and engage with Albertans to learn about their experiences. Health Quality Alberta's responsibilities are outlined in the Health Quality Council of Alberta Act. We encourage you to visit their website (https://hqa.ca/) to learn more about them, their survey and measurement work, and the variety of products they produce.About the ProjectAlberta's health system monitoring remains largely retrospective and dashboard-driven. System leaders increasingly need to ask real-time questions about capacity, trends, variation, and service pressures, yet current tools are limited in how much they can provide without analyst support.This project will be focused on the development and implementation of an AI-enabled chatbot overlay on existing dashboards to support self-directed analytics using natural-language queries. The goal is to deliver immediate value by improving accessibility, usability, and interpretation of existing health system data. This project will also establish the technical, governance, and user-interaction foundations required to de-risk and accelerate future development.Required Skills / ExpertiseWe're looking for a talented and enthusiastic individual with solid knowledge of machine learning, demonstrated experience with NLP, LLMs, and familiar with healthcare data.Key Responsibilities: Design and implement RAG-based approaches for dynamically retrieving schema metadata to semantically enrich the context for LLM prompts in the text-to-sql engine. Develop syntactic validation of SQL results and implement an iterative agentic loop for self-correction. Benchmark and validate results using different LLM models, and SQL queries of increasing complexity. Curate domain-specific SQL queries to develop an SFT pipeline, and assess performance advantages. Identify, prepare, and optimize large structured and unstructured datasets for ML modeling. Conduct applied research on ML techniques, with a focus on understanding and addressing the limitations of existing models. Collaborate with project team and stakeholders to develop minimum viable products (MVPs) and client focused solutions. Engage in regular client meetings, contributing to presentations and reports on project progress. Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities. Support the productionalization and deployment of models in client environment. Develop an understanding of Administrative Health data, including but not limited to Discharge Abstract Database (DAD), National Ambulatory Care Reporting System (NACRS), Practitioner Claims, and more. Required Qualifications: Completion of a Computing Science or ML graduate program, MSc. or PhD. Research or project experience in machine learning, specifically using NLP tools and techniques. Ability to craft zero-shot/few-shot prompts, chain-of-thought logic, and schema-linking techniques. Familiarity with working with database schemas. Working knowledge of LLM-based tools and agentic workflows. Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, Keras, Tensorflow, PyTorch, Pandas, Jupyter notebooks). Familiarity with linux, Git version control, and writing clean code. A positive attitude towards learning and understanding a new applied domain. Must be able to work full time in person at the Calgary office. Must be legally eligible to work in Canada. Preferred Qualifications: Publication record in peer-reviewed academic conferences or relevant journals in machine learning. Familiarity with the healthcare system data (nice to have). Non-Technical Requirements: Desire to take ownership of a problem and demonstrated 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 ML 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 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) About 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.How to ApplyIf this sounds like the opportunity you've been waiting for, please don't wait for the closing July 28, 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.