Morphace builds wearable devices that track skin hydration and rejuvenation signals. Our device streams numeric data (via Bluetooth) to an iOS app, which stores everything in an AWS RDS (PostgreSQL) database through a small REST API.

Working alongside our internal team of 2 software engineers over the summer, your focus is to integrate our existing code and optimize existing features for response time. As the core feature is data visualization and trend analysis, there is potential to implement existing ML models for numerical trend detection.

Tasks

• Deploy our existing REST API code securely for accessing our database (postgreSQL, AWS RDS)
• Merge existing trend-detection functions in Python with existing code in Swift
• Integrate existing UI/UX code with existing code for core and additional features
• Profile our existing overall end-to-end pipeline (iOS → API → DB) and suggest ways to remove redundant calls, shrink payloads, and improve caching
• (Optional) Build a modular cleaning pipeline (outlier removal, resampling, unit conversion) so future ML models can plug in with minimal effort

Final deliverables

1. API Endpoints: fully functional routes for the iOS App to call & edit the database
2. Test Cases: major functions unit tested
3. Deployed Backend and Frontend: live instances ready for use