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Junior Machine Learning Engineer Jobs in British Columbia

We are looking for a Junior Data Analyst to help turn field and lab data into actionable insights ... Familiarity with PyTorch Lightning or similar machine learning frameworks * Programming experience ...

We are looking for a Junior Data Analyst to help turn field and lab data into actionable insights ... Familiarity with PyTorch Lightning or similar machine learning frameworks * Programming experience ...

Leverage automation, machine learning or artificial intelligence to reduce manual effort and time ... Escalate issues to Senior Engineers and Support Partners as required. * Roll-out code changes, bug ...

Leverage automation, machine learning or artificial intelligence to reduce manual effort and time ... Escalate issues to Senior Engineers and Support Partners as required. * Roll-out code changes, bug ...

Junior Data Technologist

Vernon, BC · On-site

CA$67K - CA$80K/yr

Leverage automation, machine learning or artificial intelligence to reduce manual effort and time ... Escalate issues to Senior Engineers and Support Partners as required. * Roll-out code changes, bug ...

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.

AI Engineer

Vancouver, BC

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 ...

Showing results 41-60

Junior Machine Learning Engineer information

See British Columbia salary details

$26K

$119.2K

$207.5K

How much do junior machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer in British Columbia is $119,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $149,000.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

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 Junior Machine Learning Engineer jobs in British Columbia?

For Junior Machine Learning Engineer jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning Engineer jobs in British Columbia look for?

The top searched job categories for Junior Machine Learning Engineer jobs in British Columbia are:

What cities in British Columbia are hiring for Junior Machine Learning Engineer jobs?

Cities in British Columbia with the most Junior Machine Learning Engineer job openings:

Infographic showing various Junior Machine Learning Engineer job openings in British Columbia as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 30% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $119,158 per year, or $57.3 per hour.

AI Engineer/Senior AI Engineer - Evisort

Workday

Vancouver, BC

Full-time

Re-posted 17 days ago


Workday rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

155th of 245 rated software companies


Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

Join the Evisort AI team at Workday, which powers Document Intelligence AI and Workday's CLM and Contract Intelligence offerings. Our mission is to change the way business deals get done. We build ground breaking AI technology that can read and understand contract language to make every part of the deal-making process from drafting, negotiating, reviewing, approving, or managing the contracts happen faster, better, with reduced risks. We build AI first products, and automate manual work, freeing up our customers time and accelerating their businesses. You will be joining the Evisort AI team, which functions as a startup within Workday. This is your opportunity to build at the pace of innovation of a startup, while backed by the enormous support and impacting Workday's incredible customer base of 70M+ users.

About the Role

As an AI Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. You will collaborate with other engineers to deliver AI solutions across Workday's product ecosystem and utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various AI pipelines. You will develop and deploy new products at scale and leverage Workday's vast computing resources on rich datasets to deliver transformative value to our customers.

In addition to contributing to feature and service development, you must have an approach of continuous improvement, passion for quality, scale, and security. You must be curious and prepared to question or challenge choices and practices where they don't make sense to you or could be improved. You also should have a product approach and strong intuition around how AI can drive a better customer experience. Lastly, a strong sense of ownership and teamwork are essential to succeed in this role.

About You

AI Engineer

Basic Qualifications:

  • 5+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation

  • 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow

  • 2+ years of professional experience in building services to host machine learning models in production at scale

  • 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases

  • 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)

  • Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Sr. AI Engineer

Basic Qualifications:

  • 8+ years of professional experience in software engineering and product-building, with a proven track record of shipping and maintaining production code at scale.
  • 3+ years of hands-on experience integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products.

Other Qualifications:

  • Bachelor's degree (Master's preferred) in Computer Science, Software Engineering, or equivalent technical field.

  • Product-First AI Mindset: Deep focus on business value, user experience, and applying deep learning or large models directly to solve practical end-user challenges.

  • System Design & Reusability: Proven ability to architect robust application layers that wrap around AI models, establishing reusable patterns for system predictability, error handling, and seamless UX integration.

  • Experimentation & Evaluation: Skilled in rapid prototyping, benchmarking model outputs against product requirements, and setting up automated evaluation metrics (e.g., assessing retrieval quality and agentic behavior).

  • Hands-on experience with production observability and monitoring tooling (e.g., Prometheus/Grafana, OpenTelemetry, Sentry, Datadog) to debug, trace, and measure live systems

  • Experience using feature-flag/experimentation platforms (e.g., LaunchDarkly) to safely roll out, A/B test, and decommission changes, including flag lifecycle and cleanup discipline

  • Familiarity with data persistence and async processing - relational databases and schema migrations (e.g., PostgreSQL), caching (e.g., Redis), and message/queue or task workflows (e.g., Celery, Kafka, SQS)

  • A track record of writing well-tested, maintainable production code with attention to code quality, security scanning, and dependency hygiene (e.g., unit/integration tests, SonarQube, dependency tooling)

  • Familiarity with full-stack development - building web UIs (e.g., React, TypeScript) and backend services/REST APIs in Python (e.g., FastAPI, Django)

  • Technical Leadership & Mentorship: Proven track record of technically leading engineering workstreams, taking ownership of the development lifecycle, and mentoring junior-to-mid level engineers.

  • Collaborative Communication: Excellent interpersonal skills, with a knack for bridging the gap between product management, design, and foundational ML infrastructure teams.

  • Thrives in Ambiguity: Highly autonomous builder capable of taking open-ended product goals and breaking them down into concrete, scalable engineering realities.

  • 1-2+ years of hands-on experience building with modern AI orchestration frameworks (e.g., LangChain, LlamaIndex, or multi-agent frameworks) and implementing advanced prompt engineering techniques to manage complex agentic workflows.

  • 4+ years of experience optimizing application performance, specifically tackling product constraints such as API latency, token management, and user interaction design.

  • 4+ years of proven experience leveraging cloud computing platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems.

  • Hands-on experience deploying and operating services in containerized, cloud-native environments (Docker, Kubernetes), with exposure to infrastructure-as-code and GitOps tooling (e.g., Terraform, Helm, ArgoCD)


Workday Pay Transparency Statement

Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: CAN.BC.VancouverPrimary Location Base Pay Range: $128,000 CAD - $192,000 CADPrimary CAN Base Pay Range: $138,000 - $208,000 CAD


Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.


What Workday employees say

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About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005