Nordstrom is looking to optimize profit while improving the customer experience by developing and implementing advanced machine learning systems and infrastructure, focusing on Merchandising, Supply Chain, and Inventory.
Requirements
- 10+ years of related experience in applied Machine Learning.
- Strong programming skills in object-oriented languages (Scala / Python / Java/ C++ or equivalent), Data engineering skills, and a firm grasp of computer science fundamentals (data structures, algorithms, databases, etc.).
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
- Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms, and models).
- Deep understanding of statistical and machine learning algorithms, and a finely honed intuition for fitting the best model class to a given situation.
- Comfortable working with and across different cloud solutions - AWS/Sagemaker and GCP/Vertex AI experience a plus.
Responsibilities
- Design, implement, and scale critical machine learning systems and infrastructure to support Nordstrom’s business, particularly in Merchandising, Supply Chain, and Inventory.
- Collaborate with cross-functional teams to set and align on machine learning platform strategies to meet company objectives.
- Stay up-to-date with the latest technology in machine learning and apply this knowledge to tackle complex problems in innovative ways.
- Collaborate with leadership to up-level the ML tech stack and improve the performance of the organization.
- Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services.
- Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management.
- Provide technical direction that influences the entire ML community.
Other
- Mentor junior engineers and promote best practices in ML operations (MLOps).
- An ability to work both independently and collaboratively.
- A broad perspective on problem-solving.
- Strong communication skills and a desire to share your knowledge with team members and others.
- Experience partnering with cross-functional teams exercising sound judgment.
