Machine Learning Engineer - Recommendations

Back

Machine Learning Engineer - Recommendations

• Remote - Americas
• Engineering & Data

About the role

Great recommendations connect people with products they'll genuinely love. As a Machine Learning Engineer on the Recommendations team, you'll build the personalization technology that powers discovery across Shop surfaces and adjacent recommendation experiences. You'll develop advanced machine learning systems spanning retrieval, ranking, and LLM-based approaches that help millions of buyers discover the right products at the right moment, while supporting millions of merchants in reaching audiences who truly want what they offer.

This is an end to end applied ML role: you'll work across data, training, offline evaluation, online experimentation, and streaming/serving infrastructure, with multiple active model families (collaborative filtering / two-tower, LLM-based candidate generation, HSTU /generative approaches, multi-objective rankers) being flighted and iterated in production.

Key Responsibilities

• Develop and optimize advanced machine learning models for recommendation systems, including retrieval and multi-objective ranking
• Build and maintain end-to-end ML pipelines, from feature engineering and training through offline evaluation, online experimentation, and production serving
• Scale LLM-based recommendation systems for production, including throughput optimization, QPS management, multi-partition workers, and operational reliability
• Collaborate closely with platform, infrastructure, and product teams to integrate ML solutions into our unified recommendations pipeline
• Research and implement innovative algorithms—including semantic/sequence models, distillation approaches, and relevance grading—to enhance recommendation quality
• Document technical insights, share best practices, and contribute to a strong experimentation culture across engineering teams

Qualifications

• Extensive experience building and deploying machine learning models for large-scale recommendation, personalization, or ranking systems
• Strong proficiency in ML frameworks including TensorFlow or PyTorch, with expert-level Python programming skills
• Hands-on experience with learning-to-rank approaches and gradient-boosted tree frameworks (XGBoost, CatBoost, LightGBM)
• Proven analytical skills for processing and extracting insights from large-scale datasets; comfort with BigQuery/dbt, feature stores, and streaming event pipelines
• Experience with statistical methods and performance optimization for ML systems at scale
• Exposure to MLOps and control planes: orchestration, infrastructure-as-code and runtime hardening
• Experience with LLM systems in production (prompt/parameter optimization, throughput scaling), semantic embeddings, two-tower architectures, or streaming serving (e.g., Flink)

Ready to help shape how millions of buyers discover what they'll love next? Join the team building the recommendation systems that make Shop feel personal at scale. 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 workork

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
• Put AI agents and tools to work on the tasks they're built for, and focus on the work only humans can do
• Embrace differences and disagreement to get shit done and move forward
• Work digital-first for your daily work

We may use AI-enabled tools to screen, select, and assess applications. All AI outputs are reviewed and validated by our recruitment team.

Shopifyhttps://www.shopify.com

We hire people, not resumes. If you think you’re right for the role, apply now