Machine Learning Researcher

Every morning, thousands of people relearn to speak with myReha, and your models listen to every attempt. Sie erwägen, sich auf diese Stelle zu bewerben Zögern Sie nicht, scrollen Sie nach unten und bewerben Sie sich so schnell wie möglich, damit Sie nichts verpassen. nyra health builds the digital tools that make neurological rehabilitation work inside and outside clinic walls: myReha, the patient therapy app, and nyra insights, the clinician platform. 100+ clinics, 100K+ patients across DACH. 3× MRR growth target for 2026. €20M Series A. Team of 30+, scaling to ~50 this year. Ownership, excellence and patients first — that’s how we drive progress together. As our ML Researcher, you’ll report to our Head of ML and own research on nyra health’s neurological speech data, taking ideas from first experiment through to models that run in myReha and nyra insights. You’ll work closely with our Engineering team to bring models into production on-device and in the cloud. You’ll also work alongside our therapists, clinicians and product team, who know the patient problems firsthand and will help you decide which ones are worth solving. You’ll collaborate directly with the founders on nyra’s ML research roadmap, and with our academic partners on publications and joint research projects. It’s a role with a lot of autonomy and real scientific ownership. Your work goes straight to patients relearning how to speak, not to a benchmark leaderboard. What you'll shape Speech and language models: Develop and improve models for neurological speech recognition, pronunciation scoring, and phoneme-level analysis — building on our proprietary models Clinical AI: Research and prototype models for therapy content generation, patient progress prediction, and clinical decision support Multimodal approaches: Explore combinations of speech, text, and behavioral signals to build richer models of patient recovery Data pipeline and evaluation: Design evaluation frameworks, build training pipelines, and establish rigorous benchmarks for model performance in clinical contexts Publication and collaboration: Contribute to scientific publications and collaborate with academic partners on research projects Production integration: Work with Engineering to deploy models into our production stack — ensuring they run reliably at scale on-device and in the cloud Research direction: Help shape nyra's ML research roadmap, identifying high-impact opportunities at the intersection of AI and neurological rehabilitation AI-native workflow: You use AI tools daily — Claude Code, Cursor, Copilot, or similar — not as a novelty, but as your default way of working. You write better code faster because of it. Multi-agent fluency: You're comfortable orchestrating multiple AI agents, chaining prompts, and building workflows where AI handles the heavy lifting while you steer the outcome. Tooling mindset: You actively shape your own dev environment — custom scripts, automation, MCP servers, CLI tools — and you're always looking for ways to remove friction from your workflow. ML research experience: MSc or PhD (or equivalent practical experience) in machine learning, speech processing, NLP, or a related field Speech and audio expertise: Strong background in speech recognition, speech synthesis, audio processing, or related areas (experience with Whisper, wav2vec, HuBERT, or similar architectures) Deep learning proficiency: Hands-on experience with PyTorch, model training at scale, and modern training techniques (LoRA, RLHF, distillation, etc.) Research rigor: Track record of publications, open-source contributions, or documented research projects Engineering skills: Ability to write clean, production-quality Python code — not just notebooks Evaluation mindset: Experience designing experiments, defining metrics, and drawing valid conclusions from data Beyond your CV Scientifically rigorous: You care about doing things right — proper evaluation, reproducibility, and honest assessment of what works and what doesn't Impact-oriented: You're motivated by building models that ship and make a difference, not just benchmarks Curious and collaborative: You enjoy working with clinicians, therapists, and product teams to understand the problems worth solving Self-directed: You can identify promising research directions, design experiments, and drive projects forward with minimal guidance Passionate about speech and language: You find the intersection of AI and human communication fascinating — especially in populations underserved by existing technology Why nyra health Where your research lands: A better pronunciation score means more accurate feedback for a patient relearning to speak, every single day. Patients first, always: We build for better patient outcomes. Your work gives our teams more time to focus on the people delivering and receiving rehabilitation. Ownership