Job Title

About Faire Faire is an online wholesale marketplace built on the belief that the future is local independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants. By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. Were looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. Work Term Winter 2026 (January 5- April 24) Role Description TheAI Platform teams mission is to make machine learning and AI at Faire fast, accurate, and accessible to all. Its goal is to enable teams at Faire to seamlessly develop and deploy a wide variety of machine learning and AI models that power Faires two-sided marketplace. The team's work spans systems such as feature store, model training and fine-tuning platform, model store, model inference service, model evaluation and model monitoring. More recently, we are also exploring the space of AI tools, agents in order to drive customer impact. Why youll love working at Faire As a Faire coop, youll have the opportunity to: Take on the responsibilities of a fulltime engineer and be treated like a permanent Faire employee from day one Work alongside talented engineers and engineering leaders, product managers, and designers on a daily basis to contribute to real projects with real impacts Be challenged to learn and grow in a fastpaced environment with supportive team members Own projects from scoping to shipping and see how your work directly impacts our customers and drives datafocused results Learn more by checking out the internships section of Faires The Craft blog or watching this video by a former Faire coop. Job Responsibilities As a member of our ML Platform team, youll play a crucial role in developing and enhancing Faires machine learning infrastructure, directly impacting our user experience and business success. Your role will involve: Building Essential AI and ML Tools: Create and refine tools and infrastructure to streamline the workflows of our data scientists and machine learning engineers Developing Scalable AI and ML Pipelines: Utilize modern tools like Airflow, AWS Batch, Spark, GPU infrastructure to build scalable machine learning pipelines for essential AI/ML workflow components such as feature engineering, model inference etc Project Design and Ownership: Based on your interests and expertise, lead a significant project that advances a specific aspect of our AI infrastructure, contributing to our evolving platform. Core Technologies: Python, Kotlin, Git, SQL, Airflow, Spark, Snowflake, Redis, DynamoDB, Terraform, AWS. Learning Environment: Were committed to teaching and growing your skills in these technologies and beyond. Examples of projects our team works on Enabling batch model inference at scale Enhancing the feature store architecture and saving storage costs by optimizing the underlying data storage layer Streamlining model deployment processes to accelerate ML iteration and speed experimentation Other Requirements In your last Coop work term, you received an excellent or outstanding You are earning an 80%+ in your computer science courses or have shown significant improvements in grades over the course of your academic career. About our selection process If your application is selected, our Talent Team will reach out to you via email to invite you to: Step1: Technical Interview (1hr) Meet 1:1 with an experienced ML engineer to discuss your ML work experience and background. Be prepared to do a technical deep dive into a past machine learning project of yours. Bonus if it leans towards ML Ops or ML infrastructure but not a requirement! Work through a pair programming exercise together. Use this CodeSignal link to prep for the technical interview (this is entirely optional). Step3: Phone Call with Recruiter (15mins) Chat 1:1 with a Faire recruiter to get your questions answered. Our recruiter will also share some additional details, including what to expect in terms of compensation. About our work model This role will be inoffice on a hybrid schedule. Starting January13,2026, all office employees will be expected to come into the office every Tuesday, Thursday, and an employeechosen third inoffice day (Monday, Wednesday, or Friday). Coop interns must be aligned with the KitchenerWaterloo or Toronto offices and live within a 56km radius of one of the offices. Competitive Pay&Perks That Go Beyond At Faire, our coop salaries range from $32$52 CAD per hour. But thats just the beginning! Heres what else you can look forward to: 3Paid Time Off (PTO) Days Because we know rest matters. Commuter Stipend Helping you get to and from the office stressfree. Phone & Internet Stipend Stay connected, on us. 80Hours of Sick Time Your wellbeing comes first. Catered Meals & Snacks Enjoy delicious food and an impressive selection of drinks in the office. Community & Fun Connect with fellow coops and Faire employees through Slack channels, game nights, and exciting social events. Targeted Degrees and Disciplines Computing: Software Engineering Electrical and Computer Engineering Software Engineering Computer Science Data Science Application Documents Required Rsum; we dont require a cover letter, but please make it easy for us to see any experience you have with Machine Learning in your resume. Equal Employment Opportunity (EEO) Faire provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. #J-18808-Ljbffr