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

DataVisor

Software Engineer - Canada

Vancouver, BC · Remote

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... As platform engineers, we are building a next-generation machine learning platform, which ...

BDO Canada

AI Engineer

Vancouver, BC · On-site

CA$77K - CA$117K/yr

Your Opportunity As an experienced AI Engineer , you will design, build, and deploy productiongrade AI solutions that bridge experimental machine learning with scalable software engineering. In this ...

Stryker

Staff Engineer, Computer Vision

Burnaby, BC · On-site

CA$105K - CA$140K/yr

We are seeking a Staff Computer Vision Engineer to provide technical guidance and contribute to the ... Design, develop, train, and integrate advanced computer vision and machine learning solutions.

New

TELUS

Senior Software Developer

Vancouver, BC · On-site

Our team includes machine learning engineers, data engineers, developers, and technical architects with diverse technical backgrounds to ensure successful public cloud project outcomes that drive AI ...

TELUS

Senior Software Developer

Burnaby, BC · On-site

Our team includes machine learning engineers, data engineers, developers, and technical architects with diverse technical backgrounds to ensure successful public cloud project outcomes that drive AI ...

KPMG

Manager, ML/AI Engineer, Data & AI

Vancouver, BC · On-site

Are you a technically strong and businessoriented Machine Learning / AI Engineer with a passion for building and scaling intelligent solutions? Our team is looking for a handson engineer with deep ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Vancouver, BC

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 Aug 9, 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 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 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 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.

More about Machine Learning Engineer jobs
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:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Vancouver, BC as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $143,663 per year, or $69.1 per hour.

Software Engineer - Canada

DataVisor

Vancouver, BC • Remote

Full-time

Medical, PTO

Posted 11 days ago

Job description

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering the total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us!

Summary:

As platform engineers, we are building a next-generation machine learning platform, which incorporates our secret sauce, UML (unsupervised machine learning) with other SML (supervised machine learning) algorithms. Our team works to improve our core detection algorithms and automate the full training process.

As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters in real-time. The platform team is responsible for developing the architecture that makes real-time UML possible. We are looking for creative and eager engineers to help us expand our novel streaming and database systems, which enable our detection capabilities.

We continue to push the boundary of what's possible in fraud detection and data processing at scale. Join us to help usher in more innovative solutions to the fraud detection space.

What you'll do:

  • Design and build machine learning systems that process data sets from the world’s largest consumer services
  • Use unsupervised machine learning, supervised machine learning, and deep learning to detect fraudulent behavior and catch fraudsters
  • Build and optimize systems, tools, and validation strategies to support new features
  • Help design/build distributed real-time systems and features
  • Use big data technologies (e.g. Spark, Hadoop, HBase, Cassandra) to build large scale machine learning pipelines
  • Develop new systems on top of real-time streaming technologies (e.g. Kafka, Flink)

Requirements

  • 1-5 years software development experience
  • 1-5 years experience in Java, Shell, Python development
  • Excellent knowledge of Relational Databases, SQL and ORM technologies (JPA2, Hibernate) is a plus
  • Experience in Cassandra, HBase, Flink, Spark or Kafka is a plus.
  • Experience in the Spring Framework is a plus
  • Experience with test-driven development is a plus

Preferred Qualifications

  • Worked on multithreaded applications i
  • Experience in Shell and Python
  • Experience in Kubernates
  • Experience in CUDA development is a plus

Benefits

Health Insurance, PTO.