Senior ML Engineer | On-Device Audio AI | Clinical Voice Biomarkers | Hybrid | €90-105k + EquityAI Futures are exclusively supporting a search for a Senior ML Engineer at a clinical AI company working at the frontier of voice-based medical diagnostics. The company has built what is now the world's largest exclusive dataset of clinical voice recordings for a specific cardiac condition - 2+ million samples. The core device has received EU Class IIa MDR approval and FDA Breakthrough Device Designation. ISO 13485 certified.The Role As Senior ML Engineer you will own the on-device audio ML pipeline end-to-end - from acoustic feature engineering and model architecture through to quantisation, optimisation, and deployment on constrained mobile hardware. You will work directly alongside the clinical and research team, using a proprietary dataset of a scale and clinical specificity that most audio ML engineers will never encounter, to push the diagnostic performance of the algorithm further and ensure it remains robust, reliable, and deployable as a certified medical device at global scale.What you will doOwn the full on-device audio ML pipeline - acoustic feature extraction, model training and evaluation, quantisation, and optimisation for deployment on standard consumer mobile hardware without cloud dependency.Develop and iterate on model architectures suited to short-duration, variable-quality clinical audio - operating across a proprietary dataset of over three million labelled voice samples from cardiac patients.Design and implement rigorous evaluation frameworks that reflect real-world clinical performance - including robustness to recording environment, device variation, background noise, accent, and patient population diversity.Work within the constraints and disciplines of a regulated medical device development process - versioned models, documented validation, audit trails, and the engineering rigour that MDR and FDA submission requires.Collaborate directly with the clinical team to understand the physiological signal being measured and ensure model development decisions are grounded in clinical evidence, not just benchmark metrics.Contribute to the technical roadmap as the algorithm expands to additional cardiac biomarkers and potentially new disease areas beyond the current indication.Your Profile5+ years in machine learning engineering with a specific focus on audio, speech, or acoustic signal processing - production systems, not research prototypes.Hands-on experience with on-device or edge ML inference - model quantisation, pruning, and optimisation for constrained hardware.Strong Python and deep learning framework depth (PyTorch or TensorFlow); experience with audio-specific libraries (librosa, torchaudio, or comparable).Rigorous approach to model evaluation - understanding of sensitivity, specificity, ROC/AUC, and the specific statistical requirements of clinical validation.Experience working in or alongside a regulated environment where engineering decisions have auditable consequences.Package & Details€90,000 – €105,000 base + equityPermanent | Hybrid.AI Futures have been engaged exclusively for this search.If this sounds like an exciting challenge to you please apply below.AI Futures | Filling the AI Skills Gap ®

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Machine Learning Engineer