Senior Manager, Ai/Ml Platform Engineering

RequirementsDescription & Requirementswho we arelululemon 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 TeamThe 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 ResponsibilitiesAs a Senior Manager, AI/ML Engineering, you lead a team of AI/ML Engineers, setting technical direction, building delivery capability, and ensuring your team produces production‑grade AI/ML systems that drive measurable business value. Your team sits at the intersection of software engineering and AI/ML — engineers who go beyond platform and MLOps work to apply existing AI models and algorithms to specific business problems, setting up training pipelines, transforming data for AI use, fine‑tuning models for performance, and orchestrating multiple algorithm steps to build end‑to‑end AI solutions.
You establish AI/ML engineering best practices spanning model development, training infrastructure, MLOps, and GenAI systems, manage performance, coach team members on engineering craft and responsible AI, and create an environment that fosters innovation and engineering excellence. You maintain strong technical credibility, partner closely with applied science, data engineering, product, and business stakeholders, and ensure AI/ML engineering work is delivered reliably at the highest quality.
Own delivery across the team's AI/ML engineering work from problem framing through to production stability — sequencing workstreams that span both AI solution building (training, fine‑tuning, algorithm orchestration) and deployment infrastructure (MLOps, serving, monitoring), managing dependencies, and making execution trade‑offs that keep programs on track
Set technical direction for the AI/ML engineering capability area — translating business and applied science requirements into engineering programs that apply existing AI models and algorithms to specific use cases, and making platform, MLOps, and architectural choices that enable reliable delivery at scale
Contribute hands‑on to critical engineering work including AI solution design, model deployment, training infrastructure, model serving, and system design problems — demonstrating best practices, unblocking the team on hard problems, and maintaining technical credibility
Establish AI/ML engineering standards — including how to set up and manage training pipelines, transform and prepare data for AI model use, fine‑tune existing models for performance on specific use cases, and orchestrate multiple algorithm steps into cohesive AI solutions
Build and maintain the operational foundation for how AI solutions are deployed and run in production — including CI/CD for ML, model drift alerting, rollback protocols, and serving reliability
Qualifications
10-12 years of applicable experience
Bachelor's degree in Computer Science, Machine Learning, Mathematics, or related technical field, or equivalent experience
Make architectural decisions for the team's AI/ML systems spanning training, serving, and integration with downstream applications, balancing performance, scalability, and cost
Prioritize AI/ML investments within the team's scope, weighing platform and tooling spend, compute infrastructure, and foundation model adoption against expected business value
Build and maintain the team's AI/ML delivery systems — covering both the AI solution pipeline (training, fine‑tuning, data preparation, algorithm orchestration) and production operations (CI/CD for ML, deployment patterns, monitoring, rollback, lifecycle management)
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 NotesAuthorization to work in Canada is required for this role.
Compensation And Benefits Package$189,740 - $249,040
annually ;
the base pay offered isbased 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, 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 arrangementIn-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.
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