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

Remitly

Senior Engineering Manager, AI/ML

Burnaby, BC · On-site

CA$200K - CA$250K/yr

As a Senior Machine Learning Engineering Manager for the Core AI/ML team, you will lead the design and delivery of the machine learning systems and frameworks that power Remitly's next generation of ...

Stryker

Sr. Staff Engineer, Computer Vision

Burnaby, BC

CA$116K - CA$154K/yr

Lead the design, development, and deployment of advanced computer vision and machine learning solutions * Provide technical leadership and mentorship across engineering teams while influencing ...

Ubc

Data Scientist

Vancouver, BC · On-site

CA$7K - CA$11K/mo

The UBC Department of Pediatrics, Division of Endocrinology, located at BC Children's Hospital invites applications for a Machine Learning Engineer to join a multidisciplinary translational research ...

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 ...

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Showing results 1-20

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 Jun 15, 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $143,663 per year, or $69.1 per hour.
Senior Deep Learning Engineer

Senior Deep Learning Engineer

Targeted Talent

Vancouver, BC • On-site, Remote

$130K - $180K/yr

Full-time

Posted 4 days ago

Job description

We're seeking top-notch engineers to join our team. As part of our group, you'll collaborate with hardware and software engineers to design, develop, and optimize software for our chip, making AI inference accessible to everyone. You'll excel in identifying and resolving functional/performance bottlenecks in complex software and hardware designs.

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model optimization pipeline. If you thrive on pushing the boundaries of AI technology, this role is for you!

Requirements:

  • Bachelor's degree in Computer Science, Engineering, or related field
  • 5+ years of experience, with at least 2 years in both deep learning and software engineering
  • Proficiency in deep learning frameworks like Tensorflow and/or PyTorch
  • Experience with CNNs, LSTMs/RNNs, Transformers
  • Strong math skills and Python proficiency
  • Experience with C/C++

Preferred Skills & Experience:

  • Master's or PhD in Computer Science, Engineering, or related field
  • Experience in embedded or low-level programming
  • Knowledge of CUDA/OpenGL
  • Experience deploying neural networks in production
  • Familiarity with model compression techniques like quantization, pruning, etc.
These are permanent full time remote positions.
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About Targeted Talent

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Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Vancouver, BC, CA

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