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Mlops Machine Learning Engineer Jobs in Vancouver, BC

Clio

Machine Learning Engineer

Vancouver, BC · Hybrid

CA$129K - CA$174K/yr

Work in an agile environment with our team of machine learning engineers, MLOps engineering and full stack developers across a variety of projects What you may have: * Hands-on experience in model ...

BDO Canada

Senior Machine Learning Engineer

Vancouver, BC · On-site

CA$84K - CA$128K/yr

Key Responsibilities MLOps and Platform Development * Design and implement end-to-end MLOps ... Advanced programming skills in Python, with practical experience using popular machine learning ...

Vancity

Machine Learning Engineer Lead

Vancouver, BC · Remote

You will work across the full ML lifecycle, including model development, feature engineering, MLOps, deployment automation, monitoring, and continuous improvement of machine learning systems. Success ...

Vancity

Senior Machine Learning Engineer

Vancouver, BC · Remote

You will work across the full ML lifecycle, including model development, feature engineering, MLOps, deployment automation, monitoring, and continuous improvement of machine learning systems. Success ...

Remitly

Senior Machine Learning Engineer

Burnaby, BC

CA$168K - CA$210K/yr

Optimize models and pipelines using MLOps best practices: automated retraining, drift detection, CI ... Machine Learning systems in production. * Strong programming skills in Python, Go, Scala or a ...

Workday, Inc.

Machine Learning Engineer

Vancouver, BC · On-site

$128 - $192/hr

About the Role As a Machine Learning Engineer on the AI Platform Context and Retrievals team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate ...

Weir

Senior Machine Learning Developer

Vancouver, BC · Hybrid

Senior Machine Learning Developer Vancouver - Hybrid Job Summary Shape the future of AI in mining by developing production-ready machine learning solutions that drive safer, smarter and more ...

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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 Engineer

Clio

Vancouver, BC • Hybrid

CA$129K - CA$174K/yr

Full-time

Medical, Dental, Vision

Re-posted 29 days ago

Job description

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely.

We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.

Summary:

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to new challenges and technologies while making an impact.
This role is available to candidates across Canada (excluding Quebec). If you are local to one of our hubs (Burnaby, Calgary, or Toronto) you will be expected to be in office minimum twice per week on one of our Anchor Days.

What your team does:

We at Clio have an amazing team that is on a mission to transform the legal experience for all, and our engineering team's goal is to deliver an incredible experience to our customers.In the AI team in Clio, we use the latest technology in the space of NLP and GenAI to provide our customers with solutions to make their work more streamlined and efficient allowing them to have more time to focus on their clients' needs.

A day in the life might look like:

  • Develop advanced machine learning models using structured and unstructured data to improve Clio's customer's experience

  • Create LLMs based solutions to help Clio's clients to save time and create efficiencies

  • Collaborate cross-functionally with engineering, product management, operations and data science to identify new ML-driven features for Clio customers

  • Work in an agile environment with our team of machine learning engineers, MLOps engineering and full stack developers across a variety of projects

What you may have:

  • Hands-on experience in model development, particularly with traditional machine learning, NLP, and transformer-based models;

  • Proficiency in data manipulation, cleaning, and preprocessing for complex unstructured datasets;

  • Experience with agentic frameworks and workflows

  • Experience working with open-source LLM foundation models and APIs for commercial LLMs, such as ChatGPT or Gemini;

  • A proven ability to quickly learn new technologies and adapt to a dynamic, fast-paced environment with distributed teams and customers;

  • A portfolio of past projects showcasing your successes, challenges, and growth as a machine learning expert;

  • Exceptional communication skills and the ability to build trust with both internal teams and external customers;

  • A strong desire to continuously learn, challenge yourself, and refine your craft as a machine learning engineer.

This posting is for an existing vacancy.

What you will find here:

Compensation is one of the main components of Clio's Total Rewards Program. We have developed a series of programs and processes to ensure we are creating fair and competitive pay practices that form the foundation of our human and high-performing culture.

Some highlights of our Total Rewards program include:

  • Competitive, equitable salary with top-tier health benefits, dental, and vision insurance

  • Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.

  • Flexible time off policy, with an encouraged 20 days off per year.

  • $2000 annual counseling benefit

  • RRSP matching and RESP contribution

  • Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

The expected salary range for this role is $129,200 to $174,800 CAD. Initial placement within the range is informed by geographic region, experience, and skillset, with room to progress as impact and tenure grow. Final offer amounts will vary based on candidate profile.

Diversity, Inclusion, Belonging and Equity (DIBE) & Accessibility

Our team shows up as their authentic selves, and are united by our mission. We are dedicated todiversity, equity and inclusion. We pride ourselves in building and fostering an environment where our teams feel included, valued, and enabled to do the best work of their careers, wherever they choose to log in from. We believe that different perspectives, skills, backgrounds, and experiences result in higher-performing teams and better innovation. We are committed to equal employment and we encourage candidates from all backgrounds to apply.

Clio provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.

Learn more about our culture atclio.com/careers

We're a Human and High Performing AI company, meaning we use artificial intelligence to improve all of our operations. In recruitment, AI helps us streamline the process for greater efficiency. However, we've built our systems to ensure that a human always reviews AI-generated output, and we never make automated hiring decisions.

Disclaimer: We only communicate with candidates through official @clio.com email addresses.

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