AI/ML Engineer

lululemon is an innovative performance apparel company focused on yoga, running, training, and other athletic pursuits. The AI/ML Engineer will design and implement AI/ML systems across the full model lifecycle, from dataset curation and model training through deployment and production monitoring. The role also involves building scalable training pipelines, deploying production models, and contributing to model serving infrastructure in collaboration with research scientists, data scientists, and product engineers.

Responsibilities

• As an AI/ML Engineer, you will contribute to the design and implementation of AI/ML systems across the full model lifecycle from dataset curation, feature engineering, and model training through evaluation, deployment, and production monitoring. You will contribute to meaningful technical decisions on model architecture, training strategies, and serving infrastructure, working with minimal supervision to deliver reliable, high-quality AI capabilities aligned to business objectives. You will collaborate closely with research scientists, data scientists, and product engineers to translate model innovations into scalable production systems, and begin to develop mentorship and knowledge-sharing habits within the team
• Design and implement end-to-end AI/ML systems covering dataset curation, feature engineering, model training, hyperparameter optimization, evaluation, deployment, and retraining
• Apply appropriate model architectures, training strategies, and optimization techniques for given tasks including classification, regression, ranking, generation, and retrieval
• Build and maintain scalable model training pipelines using distributed training frameworks (PyTorch Distributed, Horovod, Ray Train) and cloud ML platforms (SageMaker, Vertex AI, Azure ML)
• Deploy models to production using CI/CD automation including A/B testing, canary rollouts, shadow deployment, and automated rollback procedures
• Contribute to implementation of model serving infrastructure meeting latency, throughput, and cost requirements using serving frameworks (TorchServe, Triton, BentoML, or equivalent)

Skills

• * Bachelor's degree in Computer Science, Machine Learning, Statistics, or related technical field, or equivalent experience; Master's degree in ML or AI beneficial
• * 4-8 years of AI/ML engineering experience designing and owning end-to-end ML systems including model training, evaluation, and production deployment, or equivalent, which includes educational experience (e.g., Master's degree)
• * Proven ability to design and implement production-grade AI/ML application components applying best-practice software engineering including CI/CD integration, automated testing, and service reliability patterns
• * Demonstrated experience with independently design model training strategies including architecture selection, optimization approach, and evaluation methodology aligned to business requirements
• * Demonstrated experience owning full model deployment lifecycle including CI/CD automation, canary releases, A/B testing, and automated rollback
• * Demonstrated ability to define ML Ops platform standards and reusable deployment templates adopted across the domain
• * Experience with common ML tools and frameworks and implementation such as Python, Spark, Airflow, MLFlow, feature stores, cloud ML platforms
• • 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
• 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

Benefits

• Permanent employees in this position may be eligible for our competitive annual bonus program, subject to program eligibility requirements.
• Permanent employees in this position may be eligible for equity offerings, subject to program eligibility requirements.
• 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
• Work is performed onsite, minimum 4 days per week.

Company Overview