Senior Machine Learning Researcher - Clinical AI & Voice Analytics
Role details
Job location
Tech stack
Job description
They are now looking for a Senior Machine Learning Researcher to join their growing R&D team and play a key role in developing clinical-grade AI models, translating cutting-edge research into deployable solutions used in real-world healthcare settings.
This is not a pure research-in-isolation role. You will sit at the intersection of machine learning research, clinical science, and product development, working closely with medical experts and product teams in a fast-moving startup environment.
What You'll Do
Research & Experimental Development:
- Design, execute, and interpret machine learning experiments on voice-based biomarkers for early detection of heart failure decompensation
- Research and prototype ML approaches aligned with clinical objectives, delivering proof-of-concept models
- Explore signal processing and voice analytics techniques to model physiological relationships between vocal features and cardiovascular states
- Design experiments grounded in clinical hypotheses, with strong emphasis on validation and reproducibility
- Maintain clean, reproducible research workflows (versioned datasets, tracked experiments, model registries)
Clinical Alignment & Translational Impact:
- Develop a strong understanding of heart failure physiology and real-world clinical workflows
- Collaborate closely with cardiologists and clinical researchers to ensure models reflect clinical reality
- Align research methods with ongoing and future clinical studies, including data acquisition and endpoint definition
- Ensure validation strategies meet clinical-grade and regulatory expectations (MDR / FDA)
ML Operations & Productization:
- Translate research outcomes into deployable ML prototypes suitable for clinical evaluation
- Build reusable, modular components (feature pipelines, model architectures) to support scalable ML workflows
- Work closely with Product and Engineering teams to ensure models meet regulatory, security, and observability requirements
Leadership & Growth Opportunities:
- Influence the scientific direction of voice analytics and clinical ML research
- Define experimentation standards and validation criteria across the R&D team
- Mentor junior researchers, students, and interns, fostering a culture of rigor and learning
- Support hiring and growth of the research team
- Present research outcomes internally and externally through publications and conferences
Requirements
- PhD in Machine Learning, Computer Science, Biomedical Engineering, Signal Processing, or a related field
- 4+ years' experience in ML research or data science (healthcare or regulated environments strongly preferred)
- Strong end-to-end experimentation experience: data preprocessing, feature engineering, model training, evaluation
- Proven track record of rigorous, reproducible research and translating findings into prototypes or publications
- Comfortable collaborating with doctors and presenting complex concepts clearly
Technical Stack:
- Python, PyTorch and/or TensorFlow, scikit-learn
- Experiment tracking tools (eg Weights & Biases)
- Audio and signal processing tools (eg librosa, OpenSmile or similar)
- Git-based workflows, Docker, and cloud platforms (GCP or similar)
Strong Plus:
- Experience with clinical workflows and regulated AI systems (MDR / FDA)
- Publications in ML for health, speech analytics, or biosignal processing
- Experience building voice analytics or digital health ML solutions
- Background or strong interest in cardiovascular health or heart failure
Benefits & conditions
- A competitive compensation package with the possibility of receiving company shares
- MacBook
- iPhone
- Access to the Urban Sports Club so you can stay fit.
- The unique opportunity to positively influence the lives of millions of people.
- A dynamic start-up with an ambitious, interdisciplinary team.