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lululemon is seeking a Staff AI/ML Engineer to define the technology AI/ML engineering approach and solve complex model development, training infrastructure, and AI system reliability challenges.
You will set domain standards for ML experimentation, model evaluation, responsible AI deployment, and GenAI system architecture as the highest contributor, shaping AI product strategy and mentoring senior engineers across teams.
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.
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.
As a Staff AI/ML Engineer, you will define the Technology AI/ML engineering approach and solve complex model development, training infrastructure, and AI system reliability challenges. You will set domain standards for ML experimentation practices, model evaluation, responsible AI deployment, and GenAI system architecture, operating as the highest individual contributor in the AI/ML engineering discipline and influencing technical direction at an organizational level. In this role, you will shape AI product strategy through deep technical expertise, develop the next generation of senior ML engineering leaders, and serve as a recognized authority both internally and in the broader AI/ML community. You will set the bar for technical innovation, responsible AI, and engineering excellence across multiple teams.
Please note: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of employment visa at this time for this role.
lululemon's compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and teamperformance. Thetypical hiring range for this position is from $211,880 - $278,090 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:
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.
In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.
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