P
AI Engineer in Healthcare Startup in Zürich 80-100
PlaynVoice
Remote (Global) 4d ago
About the role
About
We are a team of entrepreneurs, psychologists, and engineers bringing joy back to therapy. At PlaynVoice, we are reshaping mental health care by combining AI with clinical expertise to make documentation a breeze. In under 2 years, our AI scribe has gone from concept to reality, gaining 500+ users in Switzerland and Germany. We are generating over 20,000 patient notes monthly. We are looking for entrepreneurs; fast, ambitious, and smart individuals who want to take care of the people who take care of our mental health.
Tasks
- Prompt Engineering & Pipeline Management:
Design, iterate, and maintain prompt systems that reliably generate high-quality clinical documentation across a growing number of templates. Build scalable prompt architectures that let us add new output formats without fragmentation. - Evaluate & Integrate AI Models:
Benchmark and select the best LLM solutions for clinical documentation. Stay on top of the rapidly evolving model landscape and assess new options. - Build Evaluation Pipelines:
Design practical evaluation processes across our data pipeline from audio and transcription to LLM-generated output. The goal isn't perfection but knowing when output is good enough. - Ensure Clinical Output Quality:
Work closely with our psychologists and product team to define what "good" looks like, ensuring features meet the real-world expectations of users. - Experiment, Ship, Iterate:
Design experiments and data labeling strategies, push them to production, measure real-world performance, and use the insights to drive the next iteration.
Requirements
- Prompt Engineering & LLM Expertise:
2+ years of deep experience in systematic prompt engineering, building structured prompt systems that produce reliable outputs at scale. - Software Engineering Foundation:
Solid engineering skills in Python and cloud infrastructure (we run on Azure). You build reliable, production‑grade systems, not just notebooks. - German Language Skills:
You need to understand Swiss German to sanity check AI-generated notes against the original audio. Strong High German for evaluating written clinical output. - Pragmatic Startup Mindset:
You know that good enough is good enough. You ship fast, iterate based on real‑world feedback, and resist over‑engineering. Ideally you've worked in an early‑stage SaaS company. - Clear Communicator:
Our team works in English day‑to‑day. You can articulate technical decisions and collaborate effectively across functions.
Benefits
- Real Impact, Fast:
500+ therapists use our product daily, your work improves their lives within days, not quarters. - Unique Problem Domain:
Clinical AI at the intersection of Swiss German speech, mental health, and regulatory requirements. - Massive Ownership:
A team of ~10 means your decisions shape the product directly. - Flexibility:
Remote‑first with flexible hours and a coworking space in Zürich when you want it. - Equity:
Meaningful stake in a high‑growth healthtech company.
Application
Please send your CV and 5‑10 sentences about why PlaynVoice, generic applications won't be considered.
Requirements
- 2+ years of deep experience in systematic prompt engineering, building structured prompt systems that produce reliable outputs at scale.
- Solid engineering skills in Python and cloud infrastructure (we run on Azure).
- You build reliable, production-grade systems, not just notebooks.
- You need to understand Swiss German to sanity check AI-generated notes against the original audio.
- Strong High German for evaluating written clinical output.
- You know that good enough is good enough.
- You ship fast, iterate based on real-world feedback, and resist over-engineering.
- Ideally you've worked in an early-stage SaaS company.
- Our team works in English day-to-day.
- You can articulate technical decisions and collaborate effectively across functions.
Responsibilities
- Design, iterate, and maintain prompt systems that reliably generate high-quality clinical documentation across a growing number of templates.
- Build scalable prompt architectures that let us add new output formats without fragmentation.
- Benchmark and select the best LLM solutions for clinical documentation.
- Stay on top of the rapidly evolving model landscape and assess new options.
- Design practical evaluation processes across our data pipeline from audio and transcription to LLM-generated output.
- Work closely with our psychologists and product team to define what "good" looks like, ensuring features meet the real-world expectations of users.
- Design experiments and data labeling strategies, push them to production, measure real-world performance, and use the insights to drive the next iteration.
Benefits
Equity
Skills
AzureLLMPython
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