Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.

This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.

As a Search Relevance Engineer at Shopify, you are at the intersection of our engineering and data science organizations. You’ll be designing and implementing cutting-edge, AI-powered search and discovery solutions, directly empowering our merchants. We're all about creating tangible solutions that make a real difference in the day to day lives of entrepreneurs.

If you thrive on change, and are constantly seeking growth and higher mastery, then this is the right place for you. At Shopify, we operate on low process and high trust, and we're not afraid to step out of our comfort zones to push the boundaries of what's possible. So if you're ready to join our team of driven crafters building world-class search and discovery experiences, then we want to hear from you.

You’ll be doing things like

• Working with data scientists and engineers to productionize cutting-edge data products via load testing, metrics analysis, and offline and online experimentation, so they can scale to support millions of buyers around the world

• Designing and implementing features to improve the relevance of search and recommendation experiences, including semantic search, query understanding, and personalization

• Building and maintaining data pipelines to power our information retrieval systems

• Tuning the ElasticSearch queries that power our search and discovery experiences

• Designing, building and crafting tools for evaluation and relevance engineering, adhering to high-quality software engineering principles and best practices

• Prioritizing and communicating to technical and non-technical audiences alike

• Mentoring engineers and data scientists
  

What you bring to the team

• Demonstrated mastery of relevance engineering, with a deep understanding of discovery and recommendation systems powered by ElasticSearch, Solr, Lucene, and/or vector databases

• Extensive experience using Python, including a strong grasp of object oriented programming (OOP) fundamentals

• An understanding of how to write efficient and optimized code with low latency requirements

• A strong software development background, with proven experience, problem-solving skills, and technical system thinking

It would be great if you have:

• End-to-end experience of training, evaluating, testing and deploying machine learning, natural language processing, document reranking, and/or generative AI products at scale

• Experience with statistical methods like regression, GLMs or experiment design and analysis, other advanced techniques are also welcome

• Exposure to other languages such as Ruby, Rails, Typescript