Sr. Machine Learning Engineer

About the role

Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list.

Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern’s ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces—including Amazon, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email press@pattern.com.

Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek’s Global Most Loved Workplaces®.

We need a Senior Machine Learning Engineer to own evaluation systems and model-side quality improvements for Pattern's generative content platform, the system that produces AI-generated titles, bullets, A+ modules, and imagery across hundreds of thousands of listings. You will build reliable evaluation systems and improvements across non-deterministic systems and you will own the model-side work that acts on what those measurements find.

This is a full-time role and will work a hybrid schedule based in Lehi, Utah.

What is a day in the life of a Senior Machine Learning Engineer? - Build and maintain the datasets, rubrics, and automated judges that evaluate the efficacy of changes to the content engine.

- Convert brand rejection reasons into structured, labeled training data that feeds the next round of model improvements.

- Find ways to quantify qualitative improvements to generated content.

- Decide and defend approval thresholds for generated content in partnership with data science and brand teams.

- Build quality gates that catch problematic outputs before they reach brand review, reducing rework cycles across the pipeline.

What will I need to thrive in this role? - Strong code and system design experience in any language or stack.

- 3+ years owning production software services end to end.

- Formal statistics or machine learning training, or a defensible equivalent depth built on the job.

- Experience engineering systems with non-deterministic outputs, where correctness has to be measured rather than assumed.

- Nice to have: Fine-tuning experience (LoRA/PEFT), hands-on LLM or generative media production work, evaluation-system ownership, multimodal evaluation, e-commerce domain knowledge, human-labeling operations, or A/B testing infrastructure.