Staff & Senior Staff Applied ML Engineer (Multiple Roles)

Austin, TX, United States

Shopify

Try Shopify free and start a business or grow an existing one. Get more than ecommerce software with tools to manage every part of your business.

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Company Description

At Shopify, our mission is to make commerce better for everyone, and this includes both merchants and buyers. We believe in making entrepreneurship easier and improving the overall shopping experience. By leveraging the potential of AI, we aim to reduce the challenges faced by merchants in building and growing their businesses. Simultaneously, we want to offer buyers an enjoyable, convenient, and secure shopping experience.  With your help, we are committed to bringing this transformative technology directly into the hands of merchants and enhancing the benefits for buyers.  

Job Description

As an Applied ML Engineer at Shopify, you'll be at the forefront of building and maintaining ML systems at scale, directly empowering our merchants. We're all about creating tangible solutions that make a real difference in the day to day lives of entrepreneurs.

If you thrive on change, and are constantly seeking growth and higher mastery, then this is the right place for you. At Shopify, we operate on low process and high trust, and we're not afraid to step out of our comfort zones to push the boundaries of what's possible. So if you're ready to join our team of driven crafters bringing the transformative power of AI to commerce, then we want to hear from you.

The number of applications for ML systems at Shopify is vast.  There are many different product lines looking for Applied AI/ML Engineers to partner with and help drive value for our merchants. Some of these include:

Sidekick

We're looking to hire someone who can provide technical leadership as we use generative AI to create purpose-built solutions for entrepreneurs. We recently announced Sidekick (Tobi, our CEO describes it best) which is a perfect example of how AI can help our merchants succeed.

Shop

Working on our direct to consumer app (Shop), the goal is to create more value for buyers and merchants. This role is focused on building the next generation of search, discovery, trust and personalization algorithms, incorporating and evolving the state of the art techniques. 

Search & Product Discovery

Shopify storefront is the front end of a Shopify store that customers interact with. It is the public-facing part of the store where customers can browse products, add items to their cart, and checkout.  Work on this team focuses on helping connect buyers to products that they are interested in through the development of online discovery, search, recommendation, conversion optimization, and ranking systems.

Ads

Leveraging multiple statistical techniques, we are helping merchants allocate budgets more effectively, target specific audiences with personalized ads, and achieve improved results in terms of ROI and ad performance. More in general, we are building data products that improve the ability of our merchants to do effective advertising.  

Financial Services

Shopify is building a financial services suite to power the Shopify economy and to meet our merchants financial needs.  As part of this initiative, we are creating proprietary machine learning algorithms to enhance underwriting capabilities for lending products like Shopify Capital and Shopify Credit. Additionally, these algorithms will bolster fraud detection and mitigation capabilities for Shopify Balance, Bill Pay, and overall risk management for our range of products and services. This work involves redefining merchant engagement with financial tools, guiding the development of machine learning models and features that will drive the next generation of financial products offered by Shopify.

If any of the above areas appeal we’d love to hear from you.  

Key outputs

  • Developing, deploying and maintaining end-to-end machine learning systems at scale
  • Producing system design and architecture of scalable AI/ML systems
  • Designing and implementing robust data pipelines for training models and fine-tuning LLMs
  • Solving high impact data problems and delivering business impact through data and machine learning products
  • Prioritizing and communicating to technical and non-technical audiences alike
  • Mentoring senior data scientists

Qualifications

  • Extensive experience in technical leadership and mentoring of junior ML engineers
  • Proven track record of successfully leading and delivering complex, scalable machine learning projects
  • End-to-end experience of training, evaluating, testing and deploying machine learning products at scale
  • Experience building data pipelines and driving ETL design decisions leveraging disparate data sources
  • Extensive experience using Python including a strong grasp of object oriented programming (OOP) fundamentals
  • Experience with the following: Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery/BigTable or equivalent, orchestration tools
  • Experience with running machine learning in parallel environments (e.g. distributed clusters, GPU optimization)

It would be great if you have:

  • Built search related products e.g. chatbots, search ranking/relevance algorithms, personalization and recommender systems
  • Previous experience using Spark (either via Scala or Pyspark)
  • Experience with statistical methods like regression, GLMs or experiment design and analysis, other advanced techniques are also welcome
  • Experience with NLP, Deep Learning, and Language Models preferred for roles focussed on generative AI features such as Sidekick, along with product discovery
  • Exposure to other languages such as Ruby, Rails, Typescript

Additional Information

All your information will be kept confidential according to EEO guidelines.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Architecture BigQuery Bigtable Chatbots Data pipelines dbt Deep Learning ETL Generative AI GPU LLMs Machine Learning ML models NLP OOP Pipelines PySpark Python Recommender systems Ruby Scala Shell scripting Spark Statistics Streaming Testing TypeScript

Perks/benefits: Career development Startup environment

Region: North America
Country: United States
Job stats:  6  0  0

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