Machine Learning Engineer

At Shopify, our Applied Machine Learning Engineers tackle the most challenging technical problems in commerce. By leveraging vast datasets and cutting-edge machine learning technologies, like multimodal LLMs, embeddings, etc., you will develop ways that redefine how merchants connect with buyers. Your work will empower merchants with advanced tools and systems that enhance search, discovery, and agents at a global scale.

As an Applied Machine Learning Engineer, you will work with petabyte-scale data and utilize state-of-the-art ML methods to build and deploy models that serve millions of users. You'll be at the forefront of AI innovation, using technologies including LLM posttraining, reinforcement learning, and model quantization, to redefine what’s possible in e-commerce.

Key Responsibilities:

• Analyze and interpret large-scale datasets to drive model development and optimization.
• Collaborate with cross-functional teams to integrate ML solutions into Shopify's core products.
• Design, build, and deploy agents and multimodal LLMs that improve merchant and buyer interactions.
• Stay current with the latest advancements in machine learning technologies and frameworks.
• Document and share technical insights and best practices across teams.

Qualifications:

• Extensive experience in building and deploying machine learning models at scale.
• Proficiency in using ML framework (e.g., TensorFlow, PyTorch) and programming languages like Python.
• Strong analytical and problem-solving skills in solving real-world product problems.
• Excellent communication skills and the ability to work in a fast-paced, collaborative environment.

Ready to deploy your next breakthrough model? Join the team that’s making commerce better for everyone.

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.

This role may require on-call work