Company Description

Rhinovate 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 Description

You 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 Are

Technical 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.

Rhinovate

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