Applied AI​/ML Scientist

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. 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  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 an Applied AI/ML Scientist, you design, develop, test, and optimize AI/ML solutions that address defined business problems, with an emphasis on applied modeling, experimentation, and translating advanced AI research into scalable, production-ready solutions. You work independently to design and adapt AI/ML approaches to build prototypes, and improve model performance, reliability, and efficiency. You use domain knowledge and collaborate with stakeholders and product teams to map the business problem to the right model and AI/ML solution approach.

You own the AI solution implementation and partner with engineering teams to integrate solutions into the broader engineering system. You contribute to solution enhancements, validate outcomes, and continuously improve models based on real world performance.

• Designing and deploying machine learning and predictive/generative AI models for demand forecasting, optimization, personalization and search, intelligent automation, and multimodal content creation and enrichment.
• Applying NLP, computer vision, multimodal, or time series modeling techniques to enterprise-scale datasets that are a mix of structured and unstructured data.
• Developing experimentation frameworks and evaluation approaches to measure business impact of AI solutions in production.
• Collaborating with product and engineering teams to embed AI models into end to end business workflows.

• Translate business challenges into AI/ML approaches by working with key SMEs and stakeholders to understand problems and map them to the right AI/ML solution approach.
• Design experiments and establish success criteria aligned with business goals.
• Develop AI/ML solutions for complex business problems applying advanced techniques to deliver measurable business impact, building production-ready models, and ensuring solutions scale effectively.
• Develop prototypes and conduct rigorous experimentation, design evaluation plan to analyze model performance, and iterate to improve accuracy, generalization, interpretability, and business impact.
• Develop end-to-end working AI/ML solutions for assigned use cases from data ingestion through inference, and partner with AI/ML engineers and software engineers to ensure seamless integration into production workflows and processes.

• Bachelor's degree in computer science, machine learning, mathematics, or related field, Masters preferred.
• 4-8 years of experience building and optimizing AI/ML solutions, or equivalent research experience, including educational experience (e.g., Master's or PhD degree).
• Demonstrated experience in evaluating and applying state-of-the-art AI/ML models and methods to develop practical, high-performing solutions to specific use-cases.
• Experience designing AI/ML approaches, conducting experiments to evaluate performance, iterating on solution design to improve performance, and translating AI-ML driven insights into business goals.
• Proven ability to navigate technical complexity within assigned solutions including data transformation and preparation, model training and fine-tuning, latency constraints, and integration requirements within established architectural patterns.
• Experience with ML implementation using commonly used tools such as Python, py Torch, cloud ML platforms and libraries, open-source toolkits.

• Acknowledge the presence of choice in every moment and take…