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Machine Learning Engineer Jobs in Vancouver, BC (NOW HIRING)

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 engineering organization. This role is for someone who is passionate about building innovative solutions ...

Machine Learning Scientist

Vancouver, BC · Remote

CA$150K - CA$200K/yr

Variational AI is searching for a machine learning scientist to join us in our quest to radically accelerate the development of new drugs through machine learning excellence. For over six years, we ...

We're forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people ...

We're forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people ...

Data Engineer 1

Langley, BC · On-site

CA$85K - CA$106K/yr

Partnering with Machine Learning Engineers, Data Scientists, and Cloud Architects to deliver models into production * Coaching, mentoring, and providing feedback to team members and junior data ...

New

Showing results 21-40

Machine Learning Engineer information

See Vancouver, BC salary details

$64.8K

$143.7K

$219.6K

How much do machine learning engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning engineer in Vancouver, BC is $143,663.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,558.00 and $166,821.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate 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 Vancouver, BC?

The most popular types of Machine Learning Engineer jobs in Vancouver, BC are:

What are popular job titles related to Machine Learning Engineer jobs in Vancouver, BC?

For Machine Learning Engineer jobs in Vancouver, BC, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Vancouver, BC look for?

The top searched job categories for Machine Learning Engineer jobs in Vancouver, BC are:

What cities near Vancouver, BC are hiring for Machine Learning Engineer jobs?

Cities near Vancouver, BC with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Vancouver, BC as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 71% Full Time, 25% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $143,663 per year, or $69.1 per hour.

Machine Learning Researcher

Vancouver, BC • On-site

Royal Bank of Canada
Banking and Credit Intermediation • 10K+ employees

Full-time

Re-posted 4 days ago


Job description

Job Description

At RBC Borealis, you'll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.

We're looking for an enthusiastic Machine Learning Researcher who's excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a Machine Learning Researcher, you're looking to channel your love of playing with real-world data into industry-disrupting solutions. We're a lab that supports research on a wide variety of theoretical and applied machine learning projects. Working in our lab will grant you unique access to massive structured and unstructured datasets with the tools and resources necessary to build game-changing statistical models.

Being part of our team means you'll also have the opportunity to publish original research in peer-reviewed academic journals and participate in conferences around the world, such as NeurIPS, ICLR, ICML, CVPR and more.

Your responsibilities include:

  • Developing novel AI solutions that facilitate impactful products;

  • Conducting original, publishable research by advancing the state-of-the-art in machine learning techniques;

  • Working with the development team to transfer research work into production;

  • Interpreting larger organizational needs and designing algorithmic solutions that can drive the next generation of banking experiences;

  • Identifying relevant new AI technologies as they become available, and disseminating them into the bank's technology capabilities.

You're our ideal candidate if you have:

  • A passion for solving open problems using data and algorithms;

  • A PhD in a sub-area of AI or demonstrated research track record by means of publications and/or sophisticated AI product experience;

  • Ability to formulate and drive a research project independently without close supervision;

  • Proficiency in Python and Deep Learning packages such as Tensorflow or PyTorch.

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, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo, and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

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.

#Ll-POST

Job Skills

Analytical Thinking, Decision Making, Detail-Oriented, Long Term Planning, Machine Learning (ML), Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations, Research Documents

Additional Job Details

Address:

401 GEORGIA ST W:VANCOUVER

City:

Vancouver

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2025-11-25

Application Deadline:

2026-10-05

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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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.

Employment Type: FULL_TIME