About JawBuddy
JawBuddy helps people with jaw pain, bruxism, neck tension, and TMJ-related symptoms follow short, personalized rehabilitation routines at home.
We are a young pre-seed startup building toward MDR Class I certification, ZPP reimbursement in Germany, Android launch, clinical validation, and a proprietary CV/AR layer for jaw, face, neck, and shoulder tracking.
Why this role exists
You would be the first engineering hire working directly with Benjamin Cadiz de Gracia, CTO and Co-Founder. This is not a detached internship or a ticket queue. You will get context, review, and scoped work, then ship small but meaningful improvements.
The immediate need is someone who can reduce execution drag across bugs, Android parity, QA, UI polish, tests, and product improvements. The strategic upside is finding someone curious enough about CV/AR to grow into the moat with us over time.
How we work
We are fully remote and async-first. That only works when people write clearly, own outcomes, and respect focus time.
We use AI coding tools daily. AI can draft implementation; you remain responsible for understanding, testing, and improving it.
First 30 days
- Onboard into the React Native and TypeScript mobile app, Node/GCP backend, admin tooling, and AI-assisted development workflow
- Ship small production fixes across UI polish, copy, translation issues, Android rendering bugs, tests, QA, or simple product improvements
- Learn how we write scoped specs, review generated code, keep PRs small, and maintain medical-software documentation habits
First 60-90 days
- Help close Android parity gaps across navigation, permissions, native-module differences, responsive UI, notifications, and device QA
- Improve engagement features such as reminders, streaks, progress feedback, and exercise completion flows
- Add or improve tests around user-facing flows, API contracts, or platform-specific behavior
- Own one small product area from problem statement to PR, then test, document, and iterate after review
CV/AR growth path
- Help with capture session processing, label management, golden-frame curation, and QA overlays
- Build small tools around model evaluation, acceptance metrics, data quality, and clinical measurement checks
- Explore pose estimation, ARKit, MediaPipe, OpenCV, CoreML, TFLite, PyTorch, camera geometry, and mobile inference
- Contribute to adaptive scoring logic, outcome tracking, exercise templates, and recommendation quality checks
Must-haves
- Strong learning velocity and ownership
- Software fundamentals: Git, readable code, debugging, tests, code review, and basic system thinking
- Comfort with TypeScript or willingness to ramp quickly
- AI-assisted builder mindset with evidence that AI tools help you produce better work
- Product judgment and care for trustworthy UX
Strong signals
- A CV/AR-related project with MediaPipe, OpenCV, pose estimation, face tracking, ARKit, Unity AR, camera calibration, PyTorch, CoreML, TFLite, or similar
- A polished mobile, frontend, or product project where the details feel considered
- Demos, write-ups, prototypes, GitHub repos, shipped features, or thoughtful experiments
- Experience with Python, GCP, Firebase, PostgreSQL, or backend APIs
- Interest in digital health, medical devices, physiotherapy, rehabilitation, or regulated software