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Mlops Machine Learning Engineer Jobs in Vancouver, BC

Clio

Manager, Machine Learning Engineering

Vancouver, BC · Remote

CA$181K - CA$272K/yr

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... Collaborate cross-functionally with MLOps engineering, product management, operations, and data ...

Workday

AI Engineer

Vancouver, BC

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 ...

Later

DevOps Engineer

Vancouver, BC · On-site

... machine learning workflows. * Help evaluate and adopt DevOps and MLOps tools that improve system efficiency, observability, developer experience, model deployment, and operational reliability.

Stryker

Staff Engineer, Computer Vision

Burnaby, BC · On-site

CA$105K - CA$140K/yr

Design, develop, train, and integrate advanced computer vision and machine learning solutions ... Experience with cloud AI/ML environments, model training pipelines, or MLOps workflows.

BDO Canada

AI Engineer

Vancouver, BC · On-site

CA$77K - CA$117K/yr

Practical experience with DevOps and MLOps practices, including Docker, Kubernetes, and CI/CD pipelines for machine learning workloads. * Familiarity with machine learning lifecycle and ...

Workday

Senior AI Engineer

Vancouver, BC

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 ...

Workday

Principal AI Engineer

Vancouver, BC

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 ...

Motorola

Director of Computer Vision

Vancouver, BC · On-site

Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ... machine learning algorithms, and the end-to-end MLOps lifecycle, including 5+ years of hands-on ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Vancouver, BC

Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

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

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

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

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

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Vancouver, BC as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Machine Learning Research Engineer

Royal Bank of Canada

Vancouver, BC • On-site

Full-time

Re-posted 29 days ago

Job description

Job Description

What's the opportunity?

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 Research Engineer who's excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a ML Research Engineer in the applied research team, you'll be part of a collaborative group who aims to deliver AI projects end to end - everything from data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. The goal is to understand the needs of our business partners and bring to life these unique and efficient solutions that can only be achieved through the use of machine learning.

Your responsibilities include:

  • Building machine learning-based software solutions;

  • Collaborating with business stakeholders to prototype machine-learning solutions rapidly;

  • Conducting comparisons to existing algorithms and baselines;

  • Reviewing, extending, and optimizing prototype solutions;

  • Collaborating with the engineering team to integrate algorithms into products;

  • Developing reusable internal tools to facilitate research prototyping;

  • Supporting projects with thorough documentation, design decisions, and capabilities.

You're our ideal candidate if you have:

  • A master's or PhD degree in computer science, mathematics, physics, economics or equivalent;

  • 2+ years of applied machine learning experience in a high-responsibility, minimal-supervision environment;

  • Experience with writing modular, robust, scalable software in Python 3.x;

  • Expertise in a few of the following areas: deep learning, natural language processing, information retrieval;

  • Experience with deep learning packages such as PyTorch, JAX, or Tensorflow;

  • 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;

  • Strong communication skills and a collaborative attitude.

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:

2026-06-23

Application Deadline:

2026-08-31

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

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