Senior Applied Machine Learning Engineer (Multiple Roles)

Company Description

At Shopify, our mission is to make commerce better for everyone, which includes both merchants and buyers. We believe in simplifying entrepreneurship and enhancing the overall shopping experience. By harnessing the power of AI, we aim to alleviate the hindrances encountered by merchants in building and growing their businesses. At the same time, we want to deliver a pleasant, convenient, and safe shopping experience for buyers. With your assistance, we are devoted to deploying this transformative technology directly to merchants and escalating the advantages for buyers.

Job Description

As an Applied ML Engineer at Shopify, you will be at the forefront of constructing and sustaining ML systems wide-scale, directly empowering our merchants. We are devoted to creating solid solutions that make a significant difference in the everyday lives of entrepreneurs.

If you thrive in dynamic environments and are persistently seeking progression and higher skills, then this is the perfect place for you. At Shopify, we operate on minimal process and high trust, and we're unafraid to step out of our comfort zones to push the limits of possibilities. So, if you're ready to join our team of motivated makers, bringing the transformative power of AI to commerce, then we want to hear from you.

The applications for ML systems at Shopify are abundant. Various product lines are seeking Applied AI/ML Engineers to collaborate with and help generate value for our merchants. Some of these include:

Sidekick

We aim to hire someone who can offer technical leadership as we utilize generative AI to create tailored solutions for entrepreneurs. We recently introduced Sidekick (), which demonstrates how AI can help our merchants flourish.

Shop

Working on our direct-to-consumer app (), the aim is to create more value for buyers and merchants. This role is focused on constructing the next generation of search, discovery, trust, and personalization algorithms, integrating and progressing state-of-the-art techniques.

Search & Product Discovery

The Shopify storefront is the public-facing part of a Shopify store that customers interact with. It allows customers to browse products, add items to their cart, and checkout. The work on this team is centered on connecting buyers with products they are interested in through the development of online discovery, search, recommendation, conversion optimization, and ranking systems.

Ads

By leveraging various statistical techniques, we are assisting merchants in budget allocation more efficiently, targeting specific audiences with personalized ads, and achieving improved results in terms of ROI and ad performance. Broadly speaking, we are building data products that boost our merchants' capability to advertise effectively.

Financial Services

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

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

Key Outcomes

• Developing, deploying, and maintaining end-to-end machine learning systems wide-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 effectively with both technical and non-technical audiences

Qualifications

• Comprehensive experience in training, evaluating, testing, and deploying machine learning products wide-scale
• Experience in building data pipelines and influencing design decisions using disparate data sources
• Proficient experience with Python, including a strong understanding 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 in operating 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
• Prior 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 is preferred for roles focused on generative AI features like 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.