Senior Machine Learning Researcher

At Noah Labs, we are pioneering a new era of digital cardiology. Our flagship technology, Noah Labs Vox, applies advanced machine learning to the human voice to detect early signs of heart failure worsening—earlier than any existing method—transforming how clinicians monitor and manage their patients. Building on a strong foundation of international clinical trials, we are entering the next chapter: bringing this breakthrough technology to market and expanding the clinical evidence base to establish Vox as the new standard of care. Together with our deployed remote monitoring platform, Noah Labs Ark—already trusted by more than 200 cardiologists and 1,000+ patients across Europe and the United States—Noah Labs Vox will scale our remote monitoring ecosystem and shape the future of cardiovascular care. Tasks 1. Core Responsibilities A. Research and Experimental Development Plan, design, execute, and interpret ML experiments on voice-based biomarkers for heart failure decompensation prediction. Research and prototype machine learning techniques aligned with clinical objectives, delivering proofs of concept for promising methods. Explore voice analytics and signal processing approaches to uncover and model physiological relationships between vocal features and cardiovascular states, with a focus on early detection of heart failure decompensation. Use data-driven clinical hypotheses to design experiments with rigorous validation and reproducibility. Collaborate closely with medical stakeholders to translate hypotheses into meaningful data experiments. Maintain a clean, reproducible development environment (versioned datasets, tracked runs, model registries). B. Clinical Insight and Translational Alignment Develop deep understanding of heart failure decompensation, including physiological mechanisms and clinical workflows for monitoring and management. Work closely with cardiologists, clinical researchers, and study coordinators to ensure model design, data acquisition, and interpretation align with real-world clinical practice. Align research methods and milestones with ongoing and planned clinical studies (data acquisition design, endpoint definition, monitoring processes). Ensure analytical pipelines, validation strategies, and results meet clinical-grade standards and comply with MDR/FDA regulatory expectations. C. ML Operations and Clinical Productization Translate research findings into actionable insights and deployable ML prototypes suitable for clinical workflows and real-world evaluation. Design and maintain reusable, modular components (feature stores, preprocessing pipelines, model architectures) to support scalable, clinical-grade ML workflows. Collaborate closely with the Product team to ensure deployment meets regulatory, security, and observability requirements for clinical environments. 2. Leadership and Growth Opportunities A. Scientific Direction and Strategic Influence Shape the research direction for voice analytics and machine learning at Noah Labs by defining methodologies, establishing experimentation standards, and ensuring alignment with company objectives. Promote scientific rigor, curiosity, and collaboration across the R&D team, ensuring technical excellence and clinical relevance. Coordinate multidisciplinary projects, define milestones, and manage interfaces with Product, Clinical, and Engineering teams. Establish rigorous validation criteria to ensure the reliability and clinical value of research outcomes. B. Mentorship and Team Development Lead and mentor team members by defining clear goals, conducting regular reviews, and fostering a culture of efficiency, accountability, and continuous learning. Supervise Master’s theses and student interns, providing structured mentorship with clear deliverables and ongoing feedback. Support hiring efforts by identifying, interviewing, and onboarding top R&D talent. C. Scientific Communication and Clinical Impact Present research outcomes and clinical insights to internal teams, senior researchers, cardiologists, and external medtech partners. Represent Noah Labs within the scientific community through publications, conference presentations, and professional engagements. Communicate progress, challenges, and strategic recommendations to the CTO and CMedO to support company-wide decision-making. Requirements A. Education and Background PhD in Machine Learning, Computer Science, Biomedical Engineering, Signal Processing, or a related discipline. Senior-level track: 4+ years of experience in ML research or data science, ideally with exposure to healthcare or regulated data environments. B. Experience and Research Practice Proven end-to-end experimentation experience: data preprocessing, feature engineering, model training, evaluation, and error analysis. Demonstrated ability to supervise students or junior researchers and lead small-scale research projects. Track record of rigorous, reproducible experimentation and translating findings into actionable prototypes or publications. Comfortable presenting to clinical partners and at scientific or startup events. C. Technical Expertise Core ML stack: Python, PyTorch/TensorFlow, scikit-learn, Weights & Biases for experiment tracking. Signal and audio analytics: Familiarity with librosa, OpenSmile, or equivalent frameworks. Infrastructure and reproducibility: Experience with Git-based workflows, continuous integration for research code, Docker, and GCP or other cloud platforms. D. Behavior and Communication Clear, structured communicator with strong writing skills and consistent documentation of decisions, assumptions, and results. Values autonomy with accountability; thrives in in-person collaboration and rapid, iterative experimentation. E. Domain Knowledge and Compliance Awareness Familiarity with clinical workflows, medical evidence standards, and exposure to MDR/FDA expectations for AI/ML systems is a strong plus. Comfortable collaborating with clinicians and translating research outcomes into study protocols or product requirements. F. Nice-to-Haves Publications or conference presentations in machine learning for health, speech analytics, or biosignal processing. Hands-on experience building voice analytics solutions in digital health settings. Research background in cardiovascular health or heart failure decompensation, with curiosity for how AI can uncover new physiological insights. Familiarity with medically regulated AI products and enthusiasm for translating cutting-edge research into real-world clinical practice. How You’ll Work with Us Reporting line: Reports to the CTO and collaborates closely with the CMedO, Product, Development, and external clinical and scientific advisors. Position: Full-time, on-site role emphasizing fast iteration, hands-on experimentation, and close cross-functional collaboration. Benefits 🫀 The unique opportunity to make a tangible impact on the lives of millions of people. 🚀 A dynamic startup with a diverse team and exceptional talent from Harvard, TUM, Meta and Stanford. 🩺 You will be working alongside some of the brightest minds and renowned researchers from the global cardiology community with the world’s best medical institutions. 💸 A competitive compensation package with meaningful company shares and long-term growth potential. 🎾 Access to Urban Sports Club to help you stay active and fit. 💻 A beautiful office in the heart of Berlin-Mitte with a high-end espresso machine, drinks, and much more. Apply Now and be a part of our mission to transform heart failure management