Job Description

About Us

At

Chapter 2

, we’re not just scaling businesses—we’re reshaping the future of talent acquisition with

passion, loyalty, and an unwavering commitment to results

. By blending people, processes, and cutting-edge technology, we’ve redefined the traditional RPO model, delivering faster, smarter, and more cost-effective solutions that exceed expectations.


As a global powerhouse, our team spans the UK, South Africa, the US, and Germany, with India as the next frontier in our ambitious expansion. Having grown 1300% in just two years, we are unstoppable fuelling our momentum with

honesty

, collaboration, and a shared vision.


We are

relentless

in our pursuit of excellence, embedding world-class talent, pioneering technology, and compelling employer branding into organizations across industries. Our approach isn’t just about recruitment—it’s about building long-term success for our clients.


We are loyal to our clients, to our vision, and most importantly, to each other—because we know that true success is built together.


Chapter 2 – A scalable talent solution.

For more information, please watch the Chapter 2 Evolution

https://youtu.be/Fiap-bVnscY

Senior Machine Learning Researcher – Clinical AI & Voice Analytics

Location:

Berlin

Type of role:

Permanent

Sector:

Digital Health / Medical Technology (Clinical AI & Machine Learning)

Working environment:

Office-based with flexibility

Breakdown of hybrid arrangement:

Hybrid (minimum 3 days in the office) or remote (less preferred)

Working days and hours:

Monday to Friday, full time

Language requirements:

Fluent in spoken and written English

Benefits:

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.

We are supporting an innovative digital health company that is redefining how heart failure is monitored and managed using advanced machine learning and voice analytics. Their technology enables earlier detection of clinical deterioration than traditional methods, improving outcomes for patients at scale.


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

What We’re Looking For

Required:

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 clinicians and presenting complex concepts clearly

Technical Stack:

Python, PyTorch and/or TensorFlow, scikit-learn Experiment tracking tools (e.g. Weights & Biases) Audio and signal processing tools (e.g. 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