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Machine Learning Engineer - HSTU
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting
What you’ll work on
Full postingDevelop and deploy generative AI, NLP and HSTU-based recommendation models at scale
Design scalable AI/ML system architectures to support these models
Build inference pipelines that process billions of events and serve real-time recommendations
Implement data pipelines for training, fine-tuning and evaluating models across diverse data sources
Optimize production models with negative sampling, ANN search and distributed GPU training
From the employer’s posting
Develop and deploy Generative AI, natural language processing, and HSTU-based recommendation models at scale
Design and implement scalable AI/ML system architectures supporting models
Build sophisticated inference pipelines that process billions of events and deliver real-time recommendations
Implement data pipelines for model training, fine-tuning, and evaluation across diverse data sources
Optimize for production through advanced techniques like negative sampling, ANN search, and distributed GPU training
What you’ll bring
All qualificationsCore experience
- Experience in building data pipelines and driving ETL design decisions using disparate data sources.
- Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
- Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).
Qualification wording
Experience in building data pipelines and driving ETL design decisions using disparate data sources.
Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).
Posting record
Report an errorActively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 20266 days ago
- Recorded sightings
- 7
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Mar 16, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Shopify is hiring
20 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- BigQuery
- dbt
Where the posting names them
- Experience in building data pipelines and driving ETL design decisions using disparate data sources. - Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools. - Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).
Your next step
Complete your application on www.shopify.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
Join Shopify's innovative team as we work on the development and implementation of state of the art HSTU models (Hierarchical Sequential Transduction Unit) to recommend the best growth drivers and action for merchants and buyers. You'll play a pivotal role in solving high-impact data problems that directly improve merchant success and consumer experience.
As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of building AI solutions that anticipate both merchant needs and personalization for 100M+ shoppers.
Key Responsibilities:
Develop and deploy Generative AI, natural language processing, and HSTU-based recommendation models at scale
Design and implement scalable AI/ML system architectures supporting models
Build sophisticated inference pipelines that process billions of events and deliver real-time recommendations
Implement data pipelines for model training, fine-tuning, and evaluation across diverse data sources (merchant events, consumer interactions, payment sequences)
Experiment with novel architectures
Optimize for production through advanced techniques like negative sampling, ANN search, and distributed GPU training
Collaborate cross-functionally with product teams, data scientists, and infrastructure engineers to deliver measurable business impact
Communicate effectively with both technical and non-technical audiences, translating complex ML concepts into actionable insights
Qualifications:
Mastery in recommendation systems, Gen AI or LLMs
End-to-end experience in training, evaluating, testing, and deploying machine learning products at scale.
Experience in building data pipelines and driving ETL design decisions using disparate data sources.
Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).
This role may require on-call work.
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 pair programming interview, using your own IDE.
This role may require on-call work.
Ready to redefine e-commerce through AI innovation? Join the team that’s making commerce better for everyone.
Source details
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- Pay
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- Location & working pattern
Americas
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