Healthcare communication is broken. At PypeAI, we are building the Operating Layer for healthcare voice first agents that manage the entire patient journey, from clinical triage to automated follow-ups. We are building the infrastructure for autonomous healthcare coordination.
As an AI Engineer, you won't be on the sidelines; you'll be at the core of our engine. You will work directly on our Voice-to-Voice (V2V) pipeline, pushing the boundaries of what's possible in real-time, empathetic, and clinically reliable AI.
- Fine-tuning Models: Optimize domain-specific LLMs and Audio Models for medical accuracy and human-like prosody.
- V2V Pipeline: Engineer the cutting edge of STT (Speech-to-Text) and TTS (Text-to-Speech) to minimize latency to sub-second levels.
- Inference at Scale: Deploy and optimize models to handle thousands of concurrent, high-stakes medical conversations.
- Edge-of-the-Map Engineering: Work on the entire pipelinefrom data synthesis to production-grade inference.
Qualification
We are looking for someone who doesn't just use AI but understands how it breathes.
- Experience: 1-5 years in AI
- You have hands-on experience with PyTorch/TensorFlow
- have fine-tuned models or trained from scratch
- You understand audio processing (sample rates, latency, codecs) and how to make AI sound human.
- You've played with Inference Optimization (vLLM, TensorRT, or similar architectures).
- You have the hunger to solve problems that don't have right LLM answers. You are comfortable with the chaos of a 0-to-1 startup and want to see your code impact real patient lives immediately.
- Interns who have built or broken things - Most Welcome!
What you can expect
- High Ownership: You will own mission-critical modules of a platform that is already live in hospitals.
- Deep Tech: Work on specialized voice agents trained on rich medical datasets, not generic chatbots.
Do want to build the future of healthcare Or want to work on Voice AI that actually matters, we want to hear from you.
