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Sr Machine Learning Engineer Jobs in Vancouver, BC

As a Senior Machine Learning Engineer, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

Senior Machine Learning Engineer

Burnaby, BC · On-site

CA$168K - CA$210K/yr

As a Senior Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine learning ...

Senior Machine Learning Engineer

Vancouver, BC · On-site

CA$84K - CA$128K/yr

Your Opportunity BDO Digital is seeking an experienced and technically proficient Senior ML ... Advanced programming skills in Python, with practical experience using popular machine learning ...

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 ...

Machine Learning Engineer

Vancouver, BC · Hybrid

CA$129K - CA$174K/yr

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 ...

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 ...

As a Junior Machine Learning Engineer on the Global AI Team, you will support the design ... Collaborate with senior AI engineers and data scientists to improve model performance, reliability ...

As a Machine Learning Engineer Lead, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

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Work with interdisciplinary teams of developers, designers, and business experts to develop ... Machine Learning engineering practices. You will act as a technical partner and lead by example ...

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Sr Machine Learning Engineer information

What is a Sr Machine Learning Engineer?

Senior Machine Learning Engineers are experienced professionals who design, develop, and implement machine learning models and systems. They work on complex problems, lead technical projects, and often mentor junior engineers. Their responsibilities include data preprocessing, model selection, algorithm development, and optimizing solutions for scalability and performance. Senior ML Engineers also collaborate closely with data scientists, software engineers, and stakeholders to integrate machine learning into products and services.

What are the key skills and qualifications needed to thrive as a Sr Machine Learning Engineer?

To thrive as a Sr Machine Learning Engineer, you need advanced expertise in machine learning theory, programming (Python, R), data modeling, and a strong background in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP), and relevant certifications (like TensorFlow Developer) is highly beneficial. Strong problem-solving skills, effective communication, and the ability to lead and mentor teams set top candidates apart. These skills ensure the ability to design scalable ML solutions, collaborate effectively, and drive impactful business outcomes.

How does a Sr Machine Learning Engineer typically collaborate with data scientists and software engineers within a project team?

Sr Machine Learning Engineers frequently act as a bridge between data scientists, who focus on model development and experimentation, and software engineers, who handle system integration and production deployment. They translate prototype models into scalable, production-ready solutions, ensuring that models are optimized for real-world performance. Collaboration often involves reviewing code, aligning on data pipeline requirements, and participating in regular team meetings to address technical and business objectives. This cross-functional teamwork is essential for delivering reliable machine learning products.

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

AspectSr Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, ML, or related fields; experience with ML frameworksBachelor's/Master's/PhD in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds models, interprets data insights for business
Industry UsageTech, finance, healthcare, e-commerceResearch, marketing, finance, tech

While both roles involve working with data and models, Sr Machine Learning Engineers focus on building and deploying scalable ML systems, whereas Data Scientists primarily analyze data and develop insights. The roles often overlap but differ in technical focus and responsibilities.

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

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

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

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

Infographic showing various Sr Machine Learning Engineer job openings in Vancouver, BC as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Machine Learning Engineer/Machine Learning Engineer III

Workday

Vancouver, BC • On-site

Full-time

Re-posted 13 days ago


Workday rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

156th 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

Agent Factory is where Workday's next chapter gets built. 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 every day. This is production-grade AI-deeply embedded into Workday's platform-not research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. You'll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.

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-functional pod, you'll own how models, agent logic, and orchestration layers come together in production-across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement. You'll implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring solutions are scalable, observable, and enterprise-ready. This role sits at the intersection of ML and platform engineering: partnering closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack. You'll stay hands-on with emerging techniques in agentic architectures while applying strong engineering judgment to turn them into systems that are reliable, explainable, and built to operate at global scale.

About You

P4, Senior Machine Learning Engineer

Basic Qualifications

7+ 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

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

4+ 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

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

Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement

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

P3, Machine Learning Engineer III

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

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

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

3+ 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

Other Qualifications:

Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases

Professional experience in independently solving ambiguous, open-ended problems and technically leading teams

Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders


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: $180,200 CAD - $270,200 CADPrimary CAN Base Pay Range: $156,000 - $234,000 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

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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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