Head of Machine Learning, Sidekick

Shopify’s mission is to make commerce better for everyone, and a core tenet of this mission is to make entrepreneurship easier. We are deeply passionate about the potential of AI to achieve this goal by significantly reducing the toil associated with building and growing a business. At Shopify, we want to bring this technology directly into the hands of merchants, and we need your help.  

Shopify is seeking an experienced ML leader to shape how we use generative AI to create purpose-built solutions for entrepreneurs. Our recent announcement regarding Sidekick is a perfect example of how AI can help our merchants succeed.

As the Head of Machine Learning for Sidekick, 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.

Key outputs:

• 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

• 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)

All your information will be kept confidential according to EEO guidelines.