lululemon Senior AI/ML Engineer
$176.76k - $232k per yearlululemon
- Lead delivery of applied AI/ML solutions, including data pipelines, model training and experimentation infrastructure, evaluation systems, production-ready pipelines and APIs, and ML Ops for monitoring models or solutions in production.
- Define ML engineering standards for model development, evaluation, and deployment; implement reusable training pipeline templates
- Design and implement model evaluation systems and tooling including benchmark suites, human evaluation workflows, and online experiment platforms in partnership with applied science teams
- Lead architecture and engineering of LLM and GenAI systems including RAG pipelines, fine-tuning infrastructure, and agentic frameworks
- Build andmaintainAI observability frameworks covering model performance, data drift, training health metrics, and responsible AI monitoring
- Build andoperatedistributed training pipelines for advanced ML and GenAI models
- Implement scalable model serving architectures for real ‑ time and batch inference
- Developing reusable MLOps components to support experimentation, deployment, monitoring, and rollback
- Partner with AI/ML scientists to productionize models while meeting accuracy, performance, reliability, and responsible AI requirements
- Bachelor's or Master's degree in computer science, machine learning, or related technical field; Master's or equivalent experience beneficial
- 6-10 years of experience building and delivering AI/ML solutions into production
- Demonstrated ability to define software engineering standards for AI/ML systems across the domain including code quality, testing requirements, service design patterns, and API contract guidelines
- Demonstrated ability to define model implementation and training standards including architecture patterns, evaluation criteria, and responsible AI assessment frameworks adopted across the domain
- 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 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.
Authorization to work in the 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 $176,760-$232,000 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, 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)
workplace arrangement In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week. #LI-AG2
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