Senior Machine Learning Engineer

We're a company of people who like to forge our own path. We invented the blue jean in 1873, and we reinvented khaki pants in 1986. We pioneered labor and environmental guidelines in manufacturing. And we work to build sustainability into everything we do. Our brands stand for freedom and self-expression around the world.

Where we lead, others follow. For more than 160 years, we've used the strength of our brands to lead with our values and make an outsized impact on the world. We employ more than 15,000 people globally to support our great brands: Levi's®, Dockers®, Denizen® and Signature by Levi Strauss & Co.™

At Levi Strauss & Co, we are revolutionizing the apparel business and redefining the way denim is made.

We are taking one of the world's most iconic brands into the next century:

from creating machine learning-powered denim finishes to using block-chain for our factory workers' wellbeing, to building algorithms to better meet the needs of our consumers and optimize our supply chain.

Be a pioneer in the fashion industry by joining our global Data, Analytics & AI startup with assets, where you will have the chance to build exciting solutions to help our Americas business and at the same time be part of a bigger, across-continents, data community.

As the Machine Learning Engineer, you will work along side the Data Science team to operationalize the Machine Learning Models in Production on a broad set of domains that power a data-driven transformation of our standard business procedures across channels and organizations. You will develop and deploy novel approaches to optimize existing machine learning systems to maximize their value and increase consumer satisfaction at every brand touchpoint. The Machine Learning Engineer will report into the Director of AI/ML Engineering.

We are open to candidates located in the following areas: Brussels Belgium, Barcelona Spain, Madrid Spain, & London UK.

About The Job

• Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance testing and A/B testing
• Identify new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset.
• Work with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and the Levi's mobile app
• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation
• Write efficient software to ship products in an iterative, continual-release environment
• Contribute to and promote good software engineering practices across the team
• Contribute to and re-use community best practices
• Embody the values and passions that characterize Levi Strauss & Co., with empathy to engage with colleagues from multiple backgrounds

Example Projects

Besides driving the transformation of Levi's into a data-driven enterprise in general, here are some specific projects you will work on and contribute to:

• Personalized in-session product recommendation engine
• Customer Segmentation
• Automated text summarization and clustering
• Next-Best offer prediction
• Design Microassortments for Next-Gen stores
• Anomaly detection and Root Cause Analysis
• Unified consumer profile with probabilistic record linkage
• Visual search for similar and complementary products

More About You

• University or advanced degree in engineering, computer science, mathematics, or a related field
• 7+ years experience developing and deploying machine learning systems into production
• Experience working with a variety of relational SQL and NoSQL databases
• Experience working with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with at least one cloud provider solution (AWS, GCP, Azure)
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Experience working in a Linux environment
• Knowledge of data pipeline and workflow management tools
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation
• Relevant working experience with Docker and Kubernetes is a big plus