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Machine Learning Engineer Jobs in British Columbia

Amgen

Sr Machine Learning Scientist

Burnaby, BC · On-site

Career Category Engineering Join Amgen's Mission of Serving Patients At Amgen, if you feel likeyou ... Machine Learning Scientist What you will do Let'sdo this.Let'schange the world.Within Amgen ...

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 ...

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Machine Learning Engineer information

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 British Columbia? The most popular types of Machine Learning Engineer jobs in British Columbia are:
What are popular job titles related to Machine Learning Engineer jobs in British Columbia? For Machine Learning Engineer jobs in British Columbia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in British Columbia look for? The top searched job categories for Machine Learning Engineer jobs in British Columbia are:
What cities in British Columbia are hiring for Machine Learning Engineer jobs? Cities in British Columbia with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in BC? For Machine Learning Engineer jobs in BC, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in British Columbia as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Machine Learning Experts - PhD - AI Training - Canada

Prolific Academic Ltd

Vancouver, BC • On-site, Remote

CA$150/hr

Full-time

Posted 6 days ago

Job description

Machine Learning Experts - PhD - AI TrainingAbout Prolific

Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world.

Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

The role

We're looking for ML / AI experts to help train and evaluate cutting-edge AI models. For this project we are seeking PhD holders who are comfortable narrating their approach to solving complex problems.

If you have the necessary experience, we'll send you a quick test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a Domain Expert where you'll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay up to $150/hr per AI task completed. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.

What you'll bring
  • A PhD (or PhD candidacy) in Machine Learning, Artificial Intelligence or a related discipline
  • Strong subject matter expertise and ability to work through complex, technical problems
  • Experience with or a strong interest in AI and machine learning is a bonus
  • Willingness to narrate your thinking out loud
  • Strong attention to detail
  • Reliable, fast internet connection and access to a computer
  • A PayPal account to receive payments from our clients
What you'll be doing in the role
  • Working through complex problems and tasks while narrating your reasoning process out loud
  • Screen-recording your approach to problems and tasks
  • Reviewing and evaluating AI-generated responses to technical problems, rating them for accuracy, depth, and reasoning quality
  • Comparing multiple model answers and selecting/justifying the best response
  • Writing improved exemplars, rationales, or structured feedback when models fall short
Why Prolific is a great platform to join as a Participant

Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using your professional expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.
Sign up directly here - https://app.prolific.com/register/participant/waitlist/?campaign_code=CGT9PJQK

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Privacy Statement

By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.