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Machine Learning Engineer Intern Jobs in Alberta

... 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 ...

... 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 ...

Systems Developer Company Overview Stream Systems (www.streamsystems.ca) is a leading-edge ... Our SimOpti intelligence platform brings AI, machine learning and simulation to power business ...

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 ...

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 ...

... generation of AI engineers, and transform finance operations. Join our team and what we'll ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

... generation of AI engineers, and transform finance operations. Join our team and what we'll ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

... machine learning workloads at Exascale? AMD is searching for talented and motivated mathematicians, scientists, and engineers to develop GPU libraries as part the open-source AMD ROCm Software ...

We are looking for a passionate and driven Environmental Sciences or Engineering student to join ... Build on your classroom knowledge through working with and learning from experienced industry ...

We are looking for a passionate and driven Environmental Sciences or Engineering student to join ... Build on your classroom knowledge through working with and learning from experienced industry ...

Documented coursework in Software Engineering, Machine learning, Algorithms & data structures, AI, Web Development * Hands-on experience with as many of the following software tools and libraries as ...

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Machine Learning Engineer Intern information

See Alberta salary details

$23K

$120.7K

$215.5K

How much do machine learning engineer intern jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer intern in Alberta is $120,739.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $164,000.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

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 Intern jobs in Alberta? For Machine Learning Engineer Intern jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Alberta look for? The top searched job categories for Machine Learning Engineer Intern jobs in Alberta are:
What cities in Alberta are hiring for Machine Learning Engineer Intern jobs? Cities in Alberta with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in Alberta as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $120,739 per year, or $58 per hour.
Principal AI Engineer

Principal AI Engineer

Royal Bank of Canada

Calgary, AB โ€ข On-site

Full-time

Re-posted 22 days ago


Job description

Job Description

What's the opportunity?

We are looking for a Principle AI Engineer to drive the development of Data engineering solutions on RBC's Enterprise Data and AI Hybrid Multi-cloud Platforms, that meet the strategic data objectives of the business. This is unique opportunity to be an impactful Data Engineering leader on a fast growing team.

The successful candidate will be responsible for leading the design, development, and implementation of data solutions, as well as lead, mentor, and grow a team of talented data engineers. This role requires strong data engineering skills and leadership, effective written and verbal communication skills, a strong work ethic and a demonstrated capability to multi-task effectively as a member of a dynamic, fast paced team.

At RBC Borealis, you'll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.

Your responsibilities include:

  • Oversee end-to-end data integration, including sourcing, lineage, transformation, and storage to enable complex AI and advanced analytics, leveraging extensive technical expertise.

  • Collaborate with Business architecture, System architecture, Business SME and Data Stewards.

  • Architect and implement agentic systems, including tool using agents, workflow orchestrators, and multi step reasoning pipelines that reliably execute business tasks.

  • Design and deliver Retrieval Augmented Generation solutions, including document ingestion, chunking, indexing, vector search, hybrid search, reranking, and grounding strategies over curated data products.

  • Build evaluation harnesses and quality gates, including offline test sets, golden datasets, regression suites, and metrics for factuality, safety, latency, cost, and business outcomes.

  • Implement observability for AI systems, including tracing across prompts and tool calls, telemetry, drift detection, and runbooks for production operations

  • Lead the build of batch and real time data pipelines, including inbound, outbound, and event driven flows that power analytics and AI use cases.

  • Design governed data products with clear contracts, documentation, lineage, and SLAs, enabling consistent consumption across domains.

  • Establish high quality ingestion, transformation, and serving patterns using lakehouse and warehouse paradigms, plus streaming where appropriate.

  • Partner with data stewards and domain teams to define data standards, quality controls, and metadata that ensure trust and reusability

  • Design and build backend services and APIs that expose data products, agent capabilities, and AI workflows as reliable, secure services.

  • Apply rigorous engineering practices, including code quality, automated testing, CI/CD, performance engineering, and secure by default design.

  • Build scalable runtime patterns for AI systems, including caching, rate limiting, concurrency control, idempotency, and graceful degradation.

  • Contribute to reference architectures, reusable libraries, and platform components that accelerate delivery across teams.

You're our ideal candidate if you have:

  • Bachelor's degree in computer science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience.

  • 10+ years of professional software engineering experience with strong Python and SQL, Spark and Databricks SQL are a plus.

  • Demonstrated experience designing and operating scalable data architectures, including schema design, dimensional modeling, and data lifecycle management.

  • Strong knowledge of algorithms and data structures, plus systems engineering fundamentals, reliability, performance, and debugging.

  • Hands on experience with data engineering platforms and tools, commonly including Python, PySpark, Databricks, Airflow, Kafka, Snowflake, and modern data integration patterns.

  • Experience building production services and APIs, including service design, authentication and authorization, and integration patterns, Node.js and Apigee are a plus.

  • Practical experience delivering AI powered systems, including one or more of:

  • RAG systems and vector search, embeddings, reranking, and grounding strategies

  • LLM application development, structured outputs, prompt and tool calling, orchestration patterns

  • AI evaluation, test harnesses, regression testing, and lifecycle management for prompts and models

  • Observability for AI systems, tracing, monitoring, alerting, and cost controls

  • Working knowledge of security and identity frameworks such as OAuth 2.0, LDAP, Kerberos, and Vault integration, with experience operating in regulated environments.

Nice to have:

  • Master's degree in computer science or equivalent experience.

  • Experience with agent frameworks and workflow patterns, such as graph based orchestration, tool routing, plan and execute loops, and human in the loop designs.

  • MLOps and LLMOps experience, including CI/CD for ML and LLM applications, model registries, feature stores, experiment tracking, and safe rollout patterns

  • Automation and DevOps experience, such as GitHub Actions, infrastructure as code, and automated QA.

  • Experience working in Agile or SAFe environments.

  • Experience with frontend or portal integration for AI experiences, for example Angular based portals, analytics integration, or enterprise enablement tooling.

What's in it for you?

  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

  • Leaders who support your development through coaching and managing opportunities;

  • Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada's AI and data innovation. As part of Canada's largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we're at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

#TECHPJ

#Ll-POST

Job Skills

Big Data Analytics, Client Counseling, Coaching Others, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Results-Oriented, Software Engineering, Software Product Design

Additional Job Details

Address:

407 8 AVE SW:CALGARY

City:

Calgary

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-04-22

Application Deadline:

2026-07-16

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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