Staff AI/ML Engineer

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 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. Select Responsibilities Include Define the technical vision and strategy for AI/ML engineering platform spanning model development, training infrastructure, serving, evaluation, and governance Solve complex AI/ML engineering challenges including large-scale training instability, serving reliability at massive scale, and novel model quality problems with no established playbook Establish AI/ML engineering standards for experiment reproducibility, model evaluation rigor, responsible AI practices, and production reliability adopted across all teams Drive capability in frontier AI/ML techniques including large-scale foundation model training, advanced fine-tuning methods, and next-generation GenAI system design Consult with applied science leaders and enterprise architects on AI system architecture decisionsprovidingexpert guidance on feasibility, trade-offs, and long-term engineering implications Lead technical design reviewsprovidingexpert guidance on ML system architecture, training strategy, and platform evolution Mentor senior and staff engineers across the domain developing AI/ML engineering leaders and building organizational capability Qualifications Bachelor's or Master's degree in Computer Science , Machine Learning, or related technical field, or equivalent experience; advanced degree ( Master's or PhD) preferred 9-12 years of AI/ML engineering experience defining AI/ML engineering strategy andestablishingstandards across the organization, or equivalent, which includes educational experience (e.g., PhD degree) Demonstrated ability to set software engineering standards for complex AI/ML application development including design patterns, testing frameworks, and service architecture adopted across all AI/ML engineering teams Demonstrated ability to set strategy for design and implementation ofhighly complexmodels with multiple AI/ML components, training infrastructure, and evaluation rigor at enterprise scale Demonstrated ability to set MLOps strategy including CI/CD standards, serving platform architecture, and deployment practices Demonstrated ability to set GenAI engineering strategy including foundation model selection, fine-tuning infrastructure, and responsible AI standards Track recordmentoring senior and staff engineers; define the mentorship and technical development strategy for the AI/ML engineering 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 achievegreat 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, akadoesn’ttake 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 $200,080-$262,610 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.

Define the technical vision and strategy for the AI/ML engineering platform, focusing on model development, training infrastructure, and governance. Solve complex engineering challenges related to large-scale training instability and serving reliability while mentoring senior engineering leaders.

Requires 9-12 years of AI/ML engineering experience with a proven track record of setting organizational standards for MLOps and GenAI strategy. A Bachelor's or Master's degree in Computer Science or Machine Learning is required, with a PhD preferred.

• Annual bonus program • Equity offerings • Career development support • Wellbeing and personal growth support • Extended health and dental benefits • Mental health plans • Paid time off • Savings and retirement plan matching • Employee discount • Fitness & yoga classes • Parenthood top-up • Development course offerings • People networks and mentorship programs

• PythonSouhaitée
• CI/CDSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• AI/ML Engineering
• Generative AI
• MLOps
• Model Development
• Training Infrastructure
• Python
• Spark
• Airflow
• MLFlow
• Foundation Model Training
• Fine-tuning
• Responsible AI
• System Architecture
• Model Evaluation
• CI/CD
• Technical Leadership

• Technology
• Engineering
• Data & Analytics
• Software
• Retail

Formation minimale

Baccalauréat

Expérience minimale

10+ ans

Postuler avant le

10 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

4 jours par semaine

Niveau d’expérience

Mid-Senior level