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Adalyon is transforming clinical trials with a behavioural-intelligence platform that extracts digital speech biomarkers. Our platform combines agentic AI, custom large language models (LLMs) and advanced speech analytics to detect early changes in cognition, mood and behaviour during clinical trials. Recent research highlights the potential of vocal biomarkers – acoustic and linguistic features such as pitch, jitter, shimmer and speech rate – to detect early signs of mental health and neurodegenerative conditions. Adalyon’s solution builds on these insights by analysing acoustic features (pitch, speech rate and pauses), semantic patterns (sentiment, coherence and vocabulary) and behavioural cues (e.g., protocol adherence) to provide real-time visibility into behavioural and mood changes. We are now looking for a hands-on ML engineer / data scientist / LLM researcher to prove that our system can detect human well-being from AI-guided audio-interview conversations. The team is small, highly specialised, and ambitious. Adalyon values deep expertise, scientific discipline, pragmatic execution, and the ability to translate research into robust evidence that can support real-world clinical use.
Job Responsibility:
Conversational design & data pipeline
Signal processing & feature extraction
Model development & integration
Validation & evidence generation
Research & innovation
Requirements:
Advanced degree PhD, postdoctoral experience, or equivalent research depth in speech technology, audio signal processing, acoustics, machine learning, data science, computational linguistics, or a related field
Audio and NLP experience – You have built systems that process raw audio and transcripts to derive actionable insights. Familiarity with prosodic and spectral features, and the ability to engineer features like jitter, shimmer and harmonic-to-noise ratio, which have been shown to correlate with cognitive and emotional conditions
Speech processing toolkits: Experience with speech processing toolkits (e.g., librosa, Kaldi, Praat) and ML frameworks (PyTorch, TensorFlow, scikit-learn) is essential
LLM expertise – Hands-on experience with large language models, including prompting, fine-tuning and integrating them into downstream ML pipelines. Ability to interpret and control LLM outputs to ensure transparency and reproducibility, avoiding the unpredictable behaviour of generic LLMs
Startup mindset – Comfortable working in an agile, evolving environment. You take initiative, think creatively and can operate with limited structure. You thrive when delivering an MVP while planning for scalable solutions
Practical programming ability, ideally in Python and relevant scientific/data tooling. You do not need to be a software engineer, but you must be able to build the systems and pipelines needed for your research.
Nice to have:
Experience with speech or vocal biomarkers, digital health, clinical trials, remote patient monitoring, patient-reported outcomes, or clinical endpoint development
Experience with psychology, psychiatry, neurology, fatigue, cognition, affect, depression, anxiety, neurodegenerative disease, or other health areas where speech may carry meaningful signal
A publication record in relevant venues such as Interspeech, ICASSP, IEEE/ACM TASLP, Speech Communication, Computer Speech & Language, clinical digital health journals, or adjacent fields
Experience in a startup, clinical research environment, biotech, pharma, medtech, or a high-paced applied research team
What we offer:
A competitive salary package that reflects your experience and the value you create
The opportunity to work with advanced AI, acoustic analysis, and speech-based biomarker technology at an early stage
A central and highly influential role with direct access to research and technology leadership
High autonomy, high visibility, and the opportunity to shape the scientific foundation of a growing company
A dynamic and flexible startup environment with room for deep technical discussion, scientific exploration, and practical impact