Applied AI/ML Scientist — Build Production‑Ready AI Solutions

Lululemon Athletica; Seattle (WA); On-site; USD 147,000 - 193,000; Full time

Benefits offered by this job

Health & dental benefits

Paid time off

Bonus program

Career development

Job summary

lululemon is seeking an Applied AI/ML Scientist to design, develop, test, and optimize AI/ML solutions addressing defined business problems. You will work independently to build prototypes, improve model performance, and collaborate with product and engineering teams to embed AI into production workflows.

The role emphasizes applied modeling, experimentation, and translating research into scalable, trusted solutions across the retail enterprise.

Qualifications

• 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.
• Demonstrated experience evaluating and applying state-of-the-art AI/ML models to real use-cases.
• Experience designing AI/ML approaches, experiments, and translating insights into business goals.

Responsibilities

• Translate business challenges into AI/ML approaches with stakeholders.
• Design experiments and establish success criteria aligned with goals.
• Develop production-ready AI/ML models and ensure scalability.
• Collaborate with product and engineering to embed models into end-to-end workflows.

Skills

Python

PyTorch

Cloud ML platforms

Experiment design

Model deployment

Data wrangling

Education

Bachelor’s degree in CS/ML/math

Master's degree preferred

4-8 years experience

Tools

Python

PyTorch

Cloud ML platforms

Open-source toolkits

Job description

lululemon is seeking an Applied AI/ML Scientist to design, develop, test, and optimize AI/ML solutions addressing defined business problems. You will work independently to build prototypes, improve model performance, and collaborate with product and engineering teams to embed AI into production workflows.

The role emphasizes applied modeling, experimentation, and translating research into scalable, trusted solutions across the retail enterprise.