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Internship Graduate Machine Learning Jobs in Alberta

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 ...

Bachelor/Graduate degree in Computer Science or Computer/Electrical Engineering or related technical fields * Extensive experience in Python programming * Experience with machine learning techniques ...

Bachelor/Graduate degree in Computer Science or Computer/Electrical Engineering or related technical fields * Extensive experience in Python programming * Experience with machine learning techniques ...

This role is an excellent opportunity for a recent graduate to develop technical expertise in ... Collaborate with team members to support project delivery and continuous learning. * Support supply ...

This is an excellent opportunity for a recent graduate or early-career HR professional looking to ... Previous HR co-op, internship, volunteer, or administrative experience is considered an asset.

This is an excellent opportunity for a recent graduate or early-career HR professional looking to ... Previous HR co-op, internship, volunteer, or administrative experience is considered an asset.

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Internship Graduate Machine Learning information

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

What are the key skills and qualifications needed to thrive as an Internship Graduate in Machine Learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What are Internship Graduate Machine Learning positions?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do Internship Graduate Machine Learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.
What are popular job titles related to Internship Graduate Machine Learning jobs in Alberta? For Internship Graduate Machine Learning jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Internship Graduate Machine Learning jobs in Alberta look for? The top searched job categories for Internship Graduate Machine Learning jobs in Alberta are:
What cities in Alberta are hiring for Internship Graduate Machine Learning jobs? Cities in Alberta with the most Internship Graduate Machine Learning job openings:
Infographic showing various Internship Graduate Machine Learning job openings in Alberta as of July 2026, with employment types broken down into 2% As Needed, 76% Full Time, 20% Part Time, and 2% Contract. Highlights an 97% Physical, and 3% Remote job distribution.

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

Alberta Machine Intelligence Institute

Calgary, AB

Full-time

Posted 11 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.