About Shopify
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.

About you
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.

Before you apply, consider if you can:

• Care deeply about what you do and about making commerce better for everyone
• Excel by seeking professional and personal hypergrowth
• Keep up with an unrelenting pace (the week, not the quarter)
• Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
• Bring critical thought and opinion
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

About the role
At Shopify, we are developing an innovative AI Personal Shopper designed to redefine the online shopping experience for buyers. Our aim is to provide an exceptional concierge service tailored to individual preferences and needs, revolutionizing how customers interact with Shop and Storefronts.

Leveraging cutting-edge AI technology, including Large Language Models (LLM) and advanced machine learning algorithms, we will harness the power of data analytics and build upon the solid platform foundation of the Assistant projects in Shopify. This enables us to deliver personalized recommendations, exclusive offers, and insightful suggestions that cater to each user's unique taste. Our AI technology will analyze user behavior, preferences, and inventory levels in real-time, ensuring that shoppers receive highly relevant and customized suggestions. Our AI Personal Shopper will be an indispensable ally for every shopper, assisting with everything from curating outfits to finding the perfect gifts.

To expedite this effort, we are seeking a Machine Learning Engineering (MLE) lead and individual contributors to join our team and help shape the future of online shopping. Together, we will create an unparalleled shopping experience that exceeds customer expectations and redefines the e-commerce landscape.

As the Director of Machine Learning for Consumer Agent, you’ll lead a team of talented machine learning and data engineers to build a robust AI assistant for Shopify, enabling merchants to receive expert advice, support, and tailored content suggestions to run their business.

You and your team won't just be working on theoretical concepts – you'll be at the forefront of implementing AI systems at scale, directly empowering our merchants. We're all about creating tangible solutions that make a real difference in the day to day lives of entrepreneurs.

What you will do:

• Leading a team of Machine Learning Engineers to produce outcomes that align with Shopify's product vision and strategic plan
• Developing and deploying Generative AI, natural language processing and machine learning models
• Producing system design and architecture of scalable AI/ML systems
• Designing and implementing data pipelines for fine-tuning LLMs
• Solving high impact data problems and delivering business impact through data and machine learning products
• Prioritizing and communicating to technical and non-technical audiences alike

Qualifications:

• Demonstrated track record of attracting top data talent (both ICs and managers), developing those people to make them even better, and managing the growth of teams
• Demonstrated mastery building data products that use generative AI, RLHF and fine-tuning LLMs
• End-to-end experience of training, evaluating, testing and deploying machine learning products at scale
• Experience building data pipelines and driving ETL design decisions leveraging disparate data sources
• Experience with the following: Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable or equivalent, orchestration tools
• Experience with running machine learning in parallel environments (e.g. distributed clusters, GPU optimization)