Company DescriptionRhinovate builds AI-powered 3D software for rhinoplasty surgeons and patients.
Our platform enables patient-specific 3D outcome visualization and realistic healing timeline simulation, reducing uncertainty, improving consultations, and aligning expectations from day one.
We already operate a functional product with regular revenue and active clinical users. The goal now is speed: moving faster, scaling harder, and upgrading the system to production-grade quality while pushing model performance forward. We are currently in discussions for our first fundraise.
Role DescriptionYou will work directly with the co-founder to accelerate the transition from a working product to a robust, scalable, production-ready platform.
This is a hands-on engineering role at the core of the stack: 3D computer vision, generative models, data pipelines, and product hardening.
Compensation is equity only (pre-seed).
What You’ll Do- Upgrade and industrialize core components: 3D face capture, mesh manipulation, surgical outcome and healing simulation, on-device UX.
- Build and maintain data and ML pipelines: ingestion, labeling, augmentation, and synthetic data generation when relevant.
- Train, tune, and evaluate models (diffusion, NeRFs, mesh-based approaches); optimize inference speed and quality.
- Define benchmarks and metrics to track accuracy, realism, and UX impact.
- Set up lightweight MLOps: experimentation tracking, error monitoring, deployment workflows.
- Harden the product: instrumentation, reliability, privacy-first architecture, rapid iteration based on real user feedback.
Who You AreTechnical background
- Strong CS / AI / ML foundation.
- Proficient in Python and at least one ML framework (PyTorch, JAX, or TensorFlow).
- Experience in one or more of the following:
- 3D computer vision (reconstruction, pose estimation, segmentation).
- Generative models (diffusion, implicit representations).
- AR or mobile 3D (ARKit, ARCore, iOS, Android).
- Bonus: C++, Swift, or Kotlin; backend and infrastructure experience (FastAPI, Firebase, AWS, or GCP).
Mindset
- Product-driven engineer: you ship, measure, and iterate.
- Comfortable in early-stage environments with imperfect systems.
- Interested in applying advanced AI and 3D tech to real clinical use cases.
Commitment & Location- ~15 hours per week during the semester, flexible around exams.
- Berkeley / Bay Area preferred; hybrid acceptable.
Compensation- Equity only (pre-seed).
- High-impact role with direct ownership over core technology and product velocity.
