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Artificial Intelligence Machine Learning Engineer Jobs in British Columbia

About the Role As a Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small, senior, cross ...

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... use artificial intelligence to improve all of our operations. In recruitment, AI helps us ...

These include cloud\-based mobility, data analytics and visualizations, artificial intelligence, and machine learning. \n \n \n \n \n \n As a project manager, you are the primary point of contact ...

These include cloud\-based mobility, data analytics and visualizations, artificial intelligence, and machine learning. \n \n \n \n \n \n As a project manager, you are the primary point of contact ...

... developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard ... and feature engineering to validation, deployment, and monitoring. These capabilities must be ...

... for delivering Artificial Intelligence (AI) and Machine Learning (ML) models that support ... and feature engineering through experimentation, validation, deployment, and monitoring. These ...

Showing results 21-40

Artificial Intelligence Machine Learning Engineer information

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in British Columbia?

For Artificial Intelligence Machine Learning Engineer jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in British Columbia look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in British Columbia are:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in British Columbia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution.

Machine Learning Software Engineer

Royal Bank of Canada

Vancouver, BC

Full-time

Re-posted 9 days ago


Job description

Job Description


What's the opportunity?

RBC Borealis is looking for an enthusiastic software developer who's excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry. As a Machine Learning Software Engineer, you'll be responsible for owning and delivering a project end to end - everything from data pre-processing and exploration, to building and scaling ML algorithms and pipelines, to deployment and monitoring of production systems. 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 cutting-edge machine learning R&D.

Your responsibilities include:

  • To build cutting edge ML solutions throughout the research and product development lifecycle;

  • To play a key role in the design and development of Borealis' machine learning products;

  • To partner with RBC Borealis's research and product teams to ensure the seamless delivery of these products;

  • To apply engineering and data best practices to build robust and scalable large-scale machine learning software systems;

  • To support projects with thorough documentation, design decisions, and technical advisory.

You're our ideal candidate if you have:

  • Experience building modular and robust software systems in Python or similar language;

  • Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;

  • Experience working across the entire ML research and product lifecycle from prototyping to production is a plus;

  • Experience building microservices, data pipelines and using relational and non-relational databases is a plus;

  • Experience working with data science tooling and deep learning frameworks is a plus;

  • Experience with DevOps engineering (CI/CD pipelines, observability, containers etc) is a plus.

What's in it for you?

  • Be part of a dynamic & flexible working environment;

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

  • 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 the AI Group

RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations. The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery - ensuring RBC remains at the frontier of AI-enabled value creation.

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.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

#Ll-POST

#TechPJ

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product Design

Additional Job Details

Address:

777 BAY ST, TH 27:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

HUMAN RESOURCES & BMCC

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-07-27

Application Deadline:

2026-09-30

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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Employment Type: FULL_TIME