Jobs in Canada

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Added 3 days ago
L
AI/ML Engineer
lululemon
Vancouver, BC
- Full-time
Experience with common ML tools and frameworks and implementation such as Python, Spark, Airflow, MLFlow, feature stores, cloud ML platforms
Added 3 days ago
B
Agentic AI Platform Specialist
Bombardier
Dorval, QC
- Full-time
Strong software engineering and automation skills, including experience with Python and/or equivalent programming languages, APIs, Git, CI/CD, testing, and infrastructure automation.
Added 3 days ago
A
Senior Member of Technical Staff – Software Development in Test
Aptiv
Ottawa, ON
- $139,400 to $174,200 CAD / year
- Full-time
Experience with test automation frameworks such as pytest and Continuous Integration tools such as Jenkins or Travis CI.
Added 3 days ago
E
Développeur logiciel
Ericsson
Montreal, QC · Quebec, QC
- Full-time
Design, develop, test, and maintain software solutions using Golang and C/C++, with Python and Java for testing and automation
Added 3 days ago
SM
RQ11859 – Systems Testing/QA Specialist – Intermediate
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Onsite – 5 Days per Week
Added 3 days ago
IG
Automation Tester
Insight Global
Waterloo, ON
- $35 to $42 CAD / hour
- Contract
Insight Global is seeking an Automation QA Tester to support a large-scale Technology Modernization (TechMod) initiative within a leading organization in the insurance industry. The program…
Added 3 days ago
E
Développeur logiciel
Ericsson
Montreal, QC
- Full-time
Design, develop, test, and maintain software solutions using Golang and C/C++, with Python and Java for testing and automation
Added 3 days ago
E
Développeur logiciel
Ericsson
Bas-Saint-Laurent, QC
- Full-time
Design, develop, test, and maintain software solutions using Golang and C/C++, with Python and Java for testing and automation
Added 3 days ago
AS
Software Engineer
AgileGrid Solutions
Canada
- Full-time
Approximately 75% of your time will be focused on hands-on engineering, including configuration, automation, integrations, and data quality. The remaining time will involve partnering with…
Added 3 days ago
T
Senior Business Intelligence Analyst
TD
Montreal, QC
- Full-time
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
Added 3 days ago
CS
Intermediate Developer
Confiar Services
Toronto, ON
- Contract
Experience with vulnerability remediation automation and scripting (PowerShell, Python, or Bash).
Added 3 days ago
TI
Technical Architect- BOX
Themesoft Inc.
Toronto, ON
- $80 CAD / hour
- Contract
You will work closely with business and technology stakeholders to design scalable, secure, and compliant content management solutions that support thousands of users across the…
Added 3 days ago
TC
Security Research Engineer
Tata Consultancy Services
Toronto, ON
- $110,000 to $120,000 CAD / year
- Full-time
Experience with LLMs, AI agents, tool calling, orchestration frameworks, APIs, cloud, containers, and security automation.
Added 3 days ago
TC
Security Researcher Engineer
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
Must Have Technical/Functional Skills
Added 3 days ago
Information Security Analyst Co-op (Winter 2027)
Magnet Forensics
Waterloo, Ontario
This is a hands-on role where you will work directly with real security alerts, incidents, network systems, and operational workflows. In parallel, you will help design and build automation…
Added 3 days ago
O
Staff Security Risk Analyst
Okta
Toronto, ON
- $128,000 to $176,000 CAD / year
- Full-time
…work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with…
Added 3 days ago
GR
Application Analyst
GO ROCK IT
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Experience with Python and/or Java development.
Added 4 days ago
M
RQ11880 - Systems Testing/QA Specialist - Senior
Maarut
Toronto, ON
- Contract
against the various components. The tester will work with the testing lead and
Added 4 days ago
M
RQ11881 - Systems Testing/QA Specialist - Senior
Maarut
Toronto, ON
- Contract
against the various components. The tester will work with the testing lead and
Added 4 days ago
OS
Data Scientist
Ontario Securities Commission
Toronto, ON · CA ON Toronto
- Full-time
· Advanced proficiency in Python, including familiarity with data science and AI libraries such as PyTorch and Transformers.
Added 4 days ago
ST
Junior Software Engineer – Full-Stack Development & AI Integration
SynMatrix Technologies Inc.
Richmond Hill, ON
- Full-time
Must have graduated or be scheduled to graduate in 2026
Added 4 days ago
AI Safety Lab Lead
National Research Council Canada
Ottawa, ON
Experience developing Python-based tooling and automation for
Added 4 days ago
Toronto - Forward Deployed Engineer - Rapid Innovation Lab
EY
Toronto, ON
You will embed with tax professionals, business stakeholders, architects and technology teams to identify opportunities for automation, develop intelligent agent-based solutions, and…
Added 4 days ago
GC
Senior Machine Learning Programmer
Game Companies
Montreal, QC
- Full-time
You will work with our team of applied research programmers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create…
Added 4 days ago
AL
Actuarial Associate
ARAG Legal Solutions Inc. (Canada)
Toronto, ON
- Full-time
Experience with regulatory and financial reporting frameworks relevant to reserving, including OSFI requirements and IFRS 17 considerations where applicable.

lululemon

AI/ML Engineer

Vancouver, BC, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 11, 2026
Posting language: English
Posted: Nov 11, 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 team is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and products that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, advanced analytics capabilities, and AI solutions across lululemon’s vertically integrated retail ecosystem, 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 an AI/ML Engineer, you will contribute to the design and implementation of AI/ML systems across the full model lifecycle from dataset curation, feature engineering, and model training through evaluation, deployment, and production monitoring. You will contribute to meaningful technical decisions on model architecture, training strategies, and serving infrastructure, working with minimal supervision to deliver reliable, high-quality AI capabilities aligned to business objectives. You will collaborate closely with research scientists, data scientists, and product engineers to translate model innovations into scalable production systems, and begin to develop mentorship and knowledge-sharing habits within the team.

Select Responsibilities Include

Design and implement end-to-end AI/ML systems covering dataset curation, feature engineering, model training, hyperparameter optimization, evaluation, deployment, and retraining
Apply appropriate model architectures, training strategies, and optimization techniques for given tasks including classification, regression, ranking, generation, and retrieval
Build and maintain scalable model training pipelines using distributed training frameworks (PyTorch Distributed, Horovod, Ray Train) and cloud ML platforms (SageMaker, Vertex AI, Azure ML)
Deploy models to production using CI/CD automation including A/B testing, canary rollouts, shadow deployment, and automated rollback procedures
Contribute to implementation of model serving infrastructure meeting latency, throughput, and cost requirements using serving frameworks (TorchServe, Triton, BentoML, or equivalent)

Qualifications

Bachelor's degree in Computer Science, Machine Learning, Statistics, or related technical field, or equivalent experience; Master's degree in ML or AI beneficial
4-8 years of AI/ML engineering experience designing and owning end-to-end ML systems including model training, evaluation, and production deployment, or equivalent, which includes educational experience (e.g., Master's degree)
Proven ability to design and implement production-grade AI/ML application components applying best-practice software engineering including CI/CD integration, automated testing, and service reliability patterns
Demonstrated experience with independently design model training strategies including architecture selection, optimization approach, and evaluation methodology aligned to business requirements
Demonstrated experience owning full model deployment lifecycle including CI/CD automation, canary releases, A/B testing, and automated rollback
Demonstrated ability to define ML Ops platform standards and reusable deployment templates adopted across the domain
Experience with common ML tools and frameworks and implementation such as Python, Spark, Airflow, MLFlow, feature stores, cloud ML platforms

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 $127,140-$166,870 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 on LinkedIn About employer

More about this job

Responsibilities

Design and implement end-to-end AI/ML systems, including data preparation, feature engineering, model training and evaluation, deployment, and production monitoring. Build scalable training and serving infrastructure, apply deployment practices such as A/B testing and canary releases, and collaborate with research, data science, and product teams to deliver reliable AI capabilities.

Requirements

Requires a bachelor's degree in a relevant technical field or equivalent experience; a master's degree in ML or AI is beneficial. Candidates should have 4–8 years of AI/ML engineering experience and demonstrate production ML system ownership, model training strategy, deployment automation, software engineering practices, and experience with common ML tools and cloud platforms.

Skills

Python
Spark
Airflow
MLflow
PyTorch Distributed
Horovod
Ray Train
Amazon SageMaker
Vertex AI
Azure Machine Learning
TorchServe
NVIDIA Triton
BentoML
Feature Engineering
Distributed Training
MLOps

Benefits

Annual Bonus
Equity Offerings
Career Development
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
End-To-End ML Systems
Dataset Curation
Feature Engineering
Model Training
Hyperparameter Optimization
Model Evaluation
Model Deployment
Production Monitoring
Classification
Regression
Ranking
Generative Models
Retrieval
Distributed Training
CI/CD
A/B Testing
Canary Releases
Shadow Deployment
Automated Rollback
Model Serving
Latency Optimization
Throughput Optimization
Cost Optimization
Cloud ML Platforms
MLOps Standards
Automated Testing
Service Reliability
Data Governance

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Work requirements

Jobs in Canada