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Added 6 mins ago
C
Director – SAP Consulting & Business Growth
CGI
Toronto, ON
- Full-time
…senior client stakeholders, identify new opportunities and lead a team of SAP consulting…
Added 6 mins ago
EV
Senior Lead, Environment Water Treatment
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7
Store Crew
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- Full-time
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MG
Manager Project Management Office
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Lead, mentor, and develop the Project Management team, including Project Managers and Project Coordinators.
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Store Crew
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- $100,000 to $120,000 CAD / year
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Added 6 mins ago
PE
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- Full-time
● Foundational HR Development: Lead the creation and implementation of core HR policies, procedures and the first comprehensive Employee Manual, ensuring relevance across our Canadian, US,…
Added 7 mins ago
C
Consultant, Events Management (15-month contract)
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Toronto, ON
- Full-time
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Added 7 mins ago
BG
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- Full-time
…in collision and glass services. As we continue to grow and lead the industry, we ensure you have the resources and the team behind you to move your career…
Added 7 mins ago
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Senior Manager, T&O M&A, Strategic Initiatives
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- Full-time
Lead and coordinate Technology & Operations activities across complex M&A transactions, including acquisitions, divestitures, separations and other strategic initiatives.
Added 7 mins ago
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Added 7 mins ago
M
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Validate procedure accuracy and completeness with the Business SME Lead, assigned specialists, Product Owner, Risk and Delivery partners.
Added 7 mins ago
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Added 7 mins ago
II
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Added 7 mins ago
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Manager, Information Security Risk
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Added 22 mins ago
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Senior BI Analytics Governance Specialist
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Added 22 mins ago
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Added 22 mins ago
US
Distribution Supervisor II
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Added 22 mins ago
FB
Assistant Department Manager - Collingwood
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lululemon

Principal AI/ML Engineer

Vancouver, BC, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 4, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Requirements

Description & Requirements

Who we are

lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people.

About This Team

The Enterprise Data & AI organization is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and services that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, AI-driven data analytics and insights, and AI solutions across lululemon’s vertically integrated retail ecosystem, while embedding strong data governance and responsible AI practices from the very beginning. By applying AI to critical business challenges and creating new, transformative AI solutions, the team helps reshape how lululemon operates. Through deep partnership with product, technology, and business teams, Enterprise Data & AI accelerates product innovation, unlocks measurable value, elevates guest and educator experiences, and drives enterprise efficiency. 

Core responsibilities

As a Principal AI/ML Engineer, you will define and drive implementation approaches for enterprise-scale AI initiatives that transform how lululemon operates and delivers value. You will leverage deep expertise in machine learning systems, generative AI, MLOps , and platform architecture to shape company-wide technical strategy and design of the enterprise AI platform and services, and AI solutions.

You will collaborate closely with enterprise architects, applied science leaders, product leaders, and engineering organizations to translate the AI strategy and priorities into scalable technical solutions. Acting as a trusted advisor across the enterprise, you will guide critical decisions related to the architecture for enterprise AI platform and services, the evolution of the AI platform, and responsible AI implementation.

You will operate as a hands-on technical leader, advisor, and thought leader, influencing organizational direction through your technical expertise, and as an individual contributor, guide the build of AI/ML engineering capabilities across the company.This role may require availability outside of standard business hours, including on-call support, based on business needs.

Select Responsibilities Include

Define the enterprise AI/ML engineering vision and implementation strategy spanning the enterprise AI platform and services, and common frameworks and tools for model development, training infrastructure, inference platforms, evaluation frameworks, and governance capabilities.
Drive implementation of major AI initiatives, ensuring scalable, reliable, secure, and cost-effective AI solutions across the enterprise.
Demonstrate expert-level coding proficiency by developing critical components of AI platforms, ML infrastructure, and production AI systems when hands-on technical leadership is required.
Partner with enterprise architects, product team, and the Data and AI team to shape company-wide AI architecture, providing deep technical expertise on implementation feasibility, operational considerations, scalability, and long-term maintainability.
Lead technical design of foundation model services, generative AI solutions, and agentic frameworks,
Challenge and improve existing AI architectures by identifying platform limitations, technical risks, and opportunities for innovation, proposing solutions that advance enterprise AI capabilities.
Provide executive-level technical advisory on complex AI investments, build-versus-buy decisions, model strategy, technology selection, responsible AI considerations, and implementation risk assessment.
Drive enterprise-wide AI/ML engineering practices including model lifecycle management, experimentation standards, evaluation methodologies, observability, reliability, and responsible AI controls.
Influence product strategy and business investment decisions through technical insights on AI feasibility, value realization, scalability, and organizational impact.
Drive engineering productivity and AI adoption across multiple teams through platform enhancements, reusable AI capabilities, automation, and reduction of systemic technical barriers.
Mentor Senior and Staff engineers while developing the next generation of AI technical leaders across the organization.
Represent lululemon externally through industry conferences, technical publications, open-source contributions, and participation in the broader AI community.

Qualifications

Bachelor’s degree in computer science, Engineering, or related field, or equivalent experience; Master's preferred.
11-15+ years of progressive software engineering and AI/ML engineering experience, including significant experience designing and operating enterprise-scale AI systems and platforms, or equivalent.
Expert-level coding ability with a track record of developing production-grade AI/ML systems, platforms, and infrastructure that solve highly complex technical and business challenges. Retail experience preferred.
Deep expertise across system design for complex ML solutions, model deployments, batch and real-time services, and evaluation frameworks.
Proven experience defining implementation strategies and execution approaches for complex, cross-organizational AI initiatives with measurable business impact.
Demonstrated ability to evaluate and guide adoption of emerging AI technologies
Deep experience analyzing complex technical trade-offs involving model quality, latency, reliability, scalability, cost optimization, privacy, and governance requirements.
Recognized expertise in implementing AI solutions combined with the ability to assess enterprise-wide implications and influence long-term technology direction.
Experience collaborating with applied science, product, architecture, security, and engineering leadership teams to deliver enterprise AI capabilities.
Advanced experience with implementing AI/ML engineering solutions using python , Spark, Airflow, MLFlow , feature stores, vector databases, model serving platforms, cloud AI services, Kubernetes, and modern MLOps tooling.

Must haves

Acknowledge the presence of choice in every moment and take personal responsibility for your life.
Possess an entrepreneurial spirit and continuously innovate to achieve great results. 
Communicate with honesty and kindness and create the space for others to do the same. 
Lead with courage, knowing the possibility of greatness is bigger than the fear of failure. 
Foster connection by putting people first and building trusting relationships. 
Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously.

Additional Notes

Authorization to work in Canada is required for this role

Compensation And Benefits Package

lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. The typical hiring range for this position is from $208,580-$273,770 annually ; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program and equity offerings, subject to program eligibility requirements.  

At Lululemon, Investing In Our People Is a Top Priority. We Believe That When Life Works, Work Works. We Strive To Be The Place Where Inclusive Leaders Come To Develop And Enable All To Be Well. Recognizing Our Teams For Their Performance And Dedication, Other Components Of Our Total Rewards Offerings Include Support Of Career Development, Wellbeing, And Personal Growth

Extended health and dental benefits, and mental health plans
Paid time off
Savings and retirement plan matching
Generous employee discount
Fitness & yoga classes
Parenthood top-up
Extensive catalog of development course offerings
People networks, mentorship programs, and leadership series (to name a few)

Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.

workplace arrangement

In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.

Apply About employer

More about this job

Responsibilities

Define the enterprise AI/ML engineering strategy and lead the design and implementation of scalable AI platforms, services, and production solutions. Advise enterprise leaders on architecture, technology choices, responsible AI, and investment decisions while mentoring engineers and advancing organization-wide AI practices.

Requirements

Requires 11–15+ years of progressive software and AI/ML engineering experience, expert production coding ability, and a track record delivering complex enterprise-scale AI systems. A bachelor’s degree in computer science, engineering, or a related field (or equivalent experience) is required, with a master’s preferred; advanced experience with modern AI/ML, cloud, and MLOps technologies is expected.

Skills

Machine Learning Systems
Generative AI
MLOps
AI Platform Architecture
Python
Spark
Airflow
MLflow
Feature Stores
Vector Databases
Model Serving
Cloud AI Services
Kubernetes
System Design
Model Evaluation
Responsible AI

Benefits

Annual Bonus
Equity Offerings
Career Development
Wellbeing Support
Extended Health Benefits
Dental Benefits
Mental Health Plans
Paid Time Off
Savings and Retirement Plan Matching
Employee Discount
Fitness and Yoga Classes
Parenthood Top-Up
Development Courses
Mentorship Programs

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Generative AI
Agentic Frameworks
MLOps
Enterprise AI Platforms
AI Governance
Responsible AI
Python
Apache Spark
Apache Airflow
MLflow
Feature Stores
Vector Databases
Model Serving
Cloud AI Services
Kubernetes
Model Lifecycle Management
Model Evaluation
Inference Platforms
Batch Processing
Real-Time Services
Observability
Scalability
Cost Optimization
Data Governance
Retail
System Architecture
AI Infrastructure
Experimentation Standards

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