Principal AI/ML Applied Scientist
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Key skills for this role
About the Role
lululemon is seeking a Principal AI/ML Applied Scientist to define and drive enterprise-level AI/ML solutions. You will invent new AI approaches, lead cross-domain initiatives, and advise executives on AI strategy.
Key Skills for This Role
Responsibilities
- Define enterprise AI/ML strategy and solution vision for key use cases, aligning investments to business priorities
- Lead research and design of AI/ML approaches for highly complex business problems
- Advance AI/ML methodologies and solution frameworks that accelerate time to value, improve scalability and re use
- Drive innovation by extending state of the art techniques, conducting original research, and inventing novel approaches
- Influence and mentor senior technical leaders, elevating organizational capability in applied AI/ML
- Partner with executive stakeholders to identify high impact opportunities, define success metrics, and ensure AI/ML investments deliver measurable business value
- Establish enterprise experimentation and validation standards that connect model performance to business outcomes
Requirements
- Bachelor's degree in computer science, data science, engineering, or related technical field, or equivalent experience; PhD preferred
- 11 15 years of AI/ML research experience in industry or equivalent academic experience
- Demonstrated ability to define enterprise level AI/ML solutions for previously unsolved problems
- Proven track record of architecting and delivering large scale, complex AI/ML systems across multiple domains
- Deep expertise in advanced AI/ML approaches including generative AI, NLP, computer vision, multimodal learning, or time series modeling
- Expert level experience with modern ML tools and ecosystems (e.g., Python, PyTorch, cloud ML platforms, distributed training/inference systems, scalable data pipelines)
- Strong understanding of production AI systems, evaluation frameworks, and responsible AI considerations
- Authorization to work in Canada
Full Job Posting
About This Team
- The Enterprise Data & AI organization owns and builds the data and AI platforms and services that enable the enterprise to operate with intelligence at scale.
- The team leads 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.
Core Responsibilities
- Define and drive solutions for enterprise level AI/ML use cases, influencing multiple solutions across one or more business domains.
- Create business impact by extending the state of the art to invent new AI solutions.
- Operate as a top technical authority and thought leader, shaping how AI/ML becomes a durable competitive advantage.
- Lead the most complex, cross domain initiatives, establish retail industry leading methodologies, and influence long term solution approaches.
Examples of Work Include
- Designing and inventing AI solutions across domains such as product design and innovation, planning and forecasting, agentic personalization and search, and multimodal content generation and enrichment.
- Defining next generation models and architectures for generative AI, multimodal systems, and large scale ML based optimization, leading to production.
- Translating emerging AI research (e.g., LLMs, multimodal learning, foundation models) into enterprise ready capabilities with measurable business outcomes.
- Acting as a strategic advisor to executives on AI opportunities, risks, trade offs, and long term capability building.
Select Responsibilities Include
- Define enterprise AI/ML strategy and solution vision for key use cases.
- Lead research and design of AI/ML approaches for highly complex business problems.
- Advance AI/ML methodologies and solution frameworks that accelerate time to value.
- Drive innovation by extending state of the art techniques and inventing novel approaches.
- Influence and mentor senior technical leaders.
- Partner with executive stakeholders to identify high impact opportunities and define success metrics.
- Establish enterprise experimentation and validation standards.
Qualifications
- Bachelor’s degree in computer science, data science, engineering, or related technical field, or equivalent experience; PhD preferred.
- 11–15 years of AI/ML research experience in industry or equivalent academic experience.
- Demonstrated ability to define enterprise level AI/ML solutions for previously unsolved problems.
- Proven track record of architecting and delivering large scale, complex AI/ML systems across multiple domains.
- Deep expertise in advanced AI/ML approaches including generative AI, NLP, computer vision, multimodal learning, or time series modeling.
- Strong experience partnering with senior business and technology leaders.
- Expert level experience with modern ML tools and ecosystems (e.g., Python, PyTorch, cloud ML platforms, distributed training/inference systems, scalable data pipelines).
- Strong understanding of production AI systems, evaluation frameworks, and responsible AI considerations.
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.
Compensation and Benefits Package
- Typical hiring range: CAD 208,580 CAD 273,770 annually.
- Eligible for competitive annual bonus program and equity offerings.
- 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.
Workplace Arrangement
- In person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.
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