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Applied Machine Learning Engineer

Machine Learning Engineer

Posted Oct 30 (16 days ago)

Key facts

Build generative AI and large-scale ML products at Shopify; the role may include on-call work.

How this salary compares

Estimated €4,130 - €7,860

Est. take-home €2,979 - €4,830

Where and how
Global
Work model
On-siteHybridRemote
Level
Languages required
English

Original job ad

Join Shopify's innovative team as we develop an AI Personal Shopper to transform the online shopping experience. Leveraging cutting-edge AI, including Large Language Models (LLM) and advanced machine learning algorithms, you'll play a pivotal role in delivering personalized recommendations and insightful suggestions tailored to individual preferences. Our goal is to redefine e-commerce by creating a concierge service that enhances how customers interact with Shop and Storefronts. As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of implementing AI systems at scale, directly empowering merchants and creating tangible solutions with real-world impact. Key Responsibilities Develop and deploy Generative AI, natural language processing, and machine learning models. Design and produce scalable AI/ML system architectures. Implement data pipelines for fine-tuning LLMs. Solve high-impact data problems, delivering business impact through data and machine learning products. Prioritize and communicate effectively with both technical and non-technical audiences. Qualifications Mastery in building data products using generative AI, RLHF, and fine-tuning 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). 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. About the discipline Engineering. It’s our DNA. Engineering isn't a department at Shopify. It's our DNA. The engineers who thrive here care about the code, the system, and the merchants relying on both. They want hard problems and uncomfortable growth. They find solutions without waiting for permission. They ship weekly. They want commerce to work better for everyone. So does our founder, Tobi, who still codes and still shapes where this thing is going. They're open source nerds. They pair program because two brains write better code than one. New tools, new models, new approaches. They experiment constantly. Most of what's standard here started as someone hacking on something. They use AI like a keyboard, reflexively and everywhere, to clear the mundane and make room for thinking. And they work in the open. The fastest way to learn here is to watch someone better than you do the work. If that sounds like you, come build with us. Infrastructure engineering Infrastructure Engineers at Shopify build and maintain the systems that handle millions of requests per second and billions of dollars in transactions. At that scale, performance gains matter and weak assumptions surface quickly. Your systems power the experience for millions of entrepreneurs and buyers every minute of every day, including peak events like Black Friday. Engineers at Shopify spend the majority of their time actually writing code to build and improve infrastructure. You’ll solve problems that don’t exist anywhere else, with challenges that push what’s possible. If that lights you up, come build with us. Growth and rewards Mastery-matched compensation. Explore rewards ~Mastery At Shopify, getting better at your craft and increasing your impact is how you grow. Twice a year, we assess both in our ~Mastery cycle, Shopify’s performance review. Achieving higher ~Mastery is a promotion, and when you earn a promotion your total rewards grow with it. Crafter and manager are equal paths, so you can pursue excellence in the craft you’re best at. Total Rewards With Flex Comp, your Rewards Wallet gives you agency over your compensation mix. Adjust your mix of cash, restricted share units, and stock options (including programs like Long-Term Equity)* to where it makes sense for you, and mix it up anytime as life and priorities change. Buying a house? Want more skin in the game? Just experimenting? It’s your call. * Flex Comp program offerings vary based on location, role, and employment type. Full details are set out in our Terms & Conditions and related plan documents. Built for real life Room for the rest of your life. Flexible work, remote by design A flexible vacation policy means most Shopifolk can take the vacation days they feel they need to recharge. If a change of everyday scenery is more your jam, Destination 90 means you can work from (almost) anywhere in the world for 90 days of the year. Your setup Your battlestation is your home base. Request the desk, chair, and AV gear you need to get shit done. Benefits You need ‘em, we’ve got ‘em. Our health and welfare benefits may include health, dental, vision, disability, and life insurance depending on your country. If you’re in a country without a package, you'll receive a monthly allowance. We also offer mental health support for you and your dependents, including immediate and confidential services like counseling and coaching sessions. Family support We offer fertility benefits globally, along with paid parental leave to welcome a new family member. Applying to work here Show us your craft. Read the candidate guide 1 Life Story The Life Story is how we understand the themes of your career journey so far, human to human. What you’ve learned, and how you made a difference. Show us the trophies and the bruises: the problems you’ve solved, the challenges you encountered, the decisions you made, and the lessons you learned along the way. 2 Craft assessment We’re looking for world-class crafters. Crafters obsessed with pursuing excellence in their field. Our craft assessment looks at your personal journey toward mastery, and your potential to go broader and deeper in novel ways. You’ll start with an online assessment, followed by a craft assessment. Show us what you do best, and how you do it. Shopify’s bar is high, and code wins arguments around here. Let your skills do the talking. 3 Craft interviews Building on your craft assessment, these interviews dive deeper into your experience and technical aptitude. Depending on the role, this may include technical deep dives focusing on projects you've previously worked on, collaborating in a design critique, exploring a dataset using SQL, or taking the lead on solving a problem with your interviewer as your co-pilot. Pssst. Extraordinary technical work speaks for itself. Skip the resume. Show us what you’ve built instead. Take the /alt path.

About the role

Summarised by JobCrawls from the job ad above.

Requirements

  • Mastery in building data products using generative AI, RLHF, and fine-tuning LLMs
  • End-to-end experience training, evaluating, testing, and deploying machine learning products at scale
  • Experience building data pipelines and making ETL design decisions across disparate data sources
  • Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable or equivalents, and orchestration tools
  • Experience running machine learning in parallel environments, such as distributed clusters and GPU optimization

Responsibilities

  • Develop and deploy generative AI, natural language processing, and machine learning models
  • Design scalable AI/ML system architectures
  • Build data pipelines for LLM fine-tuning
  • Solve high-impact data problems and deliver business impact through data and machine learning products
  • Prioritize work and communicate effectively with technical and non-technical audiences

Skills & technologies

Generative AINatural Language ProcessingMachine LearningRLHFLLM Fine-tuningPythonShell ScriptingStreaming Data Pipelines
Show 9 more
Batch Data PipelinesVector DatabasesDbtBigQueryBigTableETLOrchestration ToolsDistributed ClustersGPU Optimization

Benefits & perks

Recruitment process

  1. Life Story
  2. Online craft assessment
  3. Craft assessment
  4. Craft interviews
  5. Pair-programming interview using your own IDE

About Shopify

Shopify logo
Shopify · 7 open roles
Top locations (all time): Remote - Global · 18 · Remote - EMEA · 3
View company
Current open roles at Shopify on JobCrawls
LocationActive listings
Remote - Global18
Remote - EMEA3
Current role mix at Shopify on JobCrawls
Role typeActive listings
Engineering Manager3
Account Executive1
Applied Machine Learning Engineer1
Compensation Analyst1
Deal Pricing Analyst1
Designer1
Enterprise Account Executive1
Executive Assistant1
Investigations Specialist1
Machine Learning Engineer1
Machine Learning Engineering Manager1
Product Management1
Product Principles1
Revenue Operations Specialist1
Sales1
Security Analyst1
Small Business Account Executive1
Software Engineer1
Technical Account Manager1
Current role-level mix at Shopify on JobCrawls
Role levelActive listings
Mid-Level9
Senior7
Manager5
About the employer

Shopify is an e-commerce company whose engineering teams build and improve systems used by merchants and buyers. Its infrastructure supports millions of requests per second and transactions worth billions of dollars.

Core values
CraftsmanshipOpen collaborationExperimentationContinuous growthMerchant impact

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