Machine Learning Engineer - HSTU

Shopify

Quick summary

Work type: On-site
Location: Ottawa, ON, Canada
Posted: 42 days ago
Nearby: 10 roles within 25 mi

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Similar $223k

$160k most similar roles pay here $278k

This listing doesn't post a salary. Most similar roles pay $195,875–$249,750.

Based on 239 similar postings.

Employer

About Shopify

Shopify is a leading global commerce platform that enables businesses of all sizes to start, grow, and manage their retail operations online and in-person. It provides tools for storefronts, payments, shipping, and marketing to millions of merchants worldwide.

Shopify currently has 25 open roles on FindRole.

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At a glance

TL;DR · Machine Learning Engineer - HSTU

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As a Machine Learning Engineering Lead or individual contributor at Shopify, you will join an innovative team focused on developing and deploying advanced HSTU models to enhance merchant growth and consumer experience. Your daily responsibilities include building scalable AI/ML system architectures, designing sophisticated inference pipelines that process billions of events in real-time, and implementing data pipelines for model training across diverse sources. You will also experiment with novel architectures, optimize production through techniques like negative sampling and distributed GPU training, and collaborate cross-functionally to deliver measurable business impact. The ideal candidate has expertise in recommendation systems, generative AI, Python, shell scripting, and experience with streaming and batch data pipelines, vector databases, and orchestration tools. This role involves working on a product that serves 100M+ users, requiring proficiency in handling large-scale data and complex technical challenges.

Skills

Python TensorFlow Keras PyTorch Scikit-learn Spark MLOps Docker Kubernetes AWS GCP CI/CD Prometheus Grafana BigQuery DBT Vector_Databases ETL Shell_Scripting

What you'll do

Develop and deploy Generative AI and HSTU-based recommendation models at scale.
Design scalable AI/ML system architectures supporting complex models.
Build inference pipelines processing billions of events for real-time recommendations.
Implement data pipelines for model training, fine-tuning, and evaluation across sources.
Optimize production processes using advanced techniques like negative sampling and ANN search.

What we're looking for

Mastery in recommendation systems and generative AI/LLMs.
Extensive experience deploying machine learning products at scale.
Expertise in building data pipelines from diverse sources.
Proficiency in Python, shell scripting, and orchestration tools.
Experience with distributed clusters and GPU optimization for ML.
Ability to communicate complex ML concepts effectively to all audiences.

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