AI Product Recommendation Website
Employer not named by the sourceRemote
Frontier is not the employer and does not collect applications.
About this role
PHP, Python, Amazon Web Services, HTML, Backend Development, Frontend Development, API Development, Data Collection · I plan to launch an e-commerce site whose standout feature is an AI-powered product recommendation engine. The model should study live user-behaviour signals—click paths, dwell time, search queries—and blend them with product metadata (titles, tags, attributes) to surface highly relevant items in real time.
A streamlined customer journey is the priority, so latency has to stay low and the suggestions must update dynamically as shoppers browse. Whether you prefer a custom Python stack with TensorFlow or a managed service such as AWS Personalize is up to you, as long as the pipeline remains transparent and can be fine-tuned once enough behavioural data accumulates.
Deliverables • Responsive e-commerce front-end connected to the recommendation API • Data-collection layer that captures user actions without slowing the site • Training and inference scripts (or configuration files) for the recommendation model • Simple admin panel to monitor key metrics and manually trigger re-training • Deployment instructions so I can reproduce the setup on a fresh server or cloud account
Acceptance criteria 1. New users see cold-start recommendations based on product metadata. 2.