Machine Learning Engineer

• Position Overview
• We’re a stealth, early-stage company building AI systems for wellbeing. We’re looking for an external Biosignal Machine Learning Research Engineer to help turn longitudinal data into reliable, useful intelligence.

• What you’ll do
• You’ll work with signals such as PPG, accelerometry, heart rate, HRV, skin temperature, and signal-quality metadata. You’ll help define the feature pipeline, benchmark modelling approaches, build personal-baseline and sleep-related time-series models, and introduce uncertainty and data-quality controls so the system knows when its output is reliable.

This is applied research with a clear path to implementation. You’ll move from literature and experimental data to reproducible code, evaluation results, and integration-ready model interfaces. You’ll also document the technical decisions and contribute selected non-proprietary tests or methods to an open-source assurance toolkit.

• Who we’re looking for
• Strong experience in machine learning, data science, signal processing, or a related quantitative field.
• Proficient in Python and comfortable building reproducible data and modelling pipelines.
• Experienced with time-series modelling, experimental design, model evaluation, and statistical reasoning.
• Able to translate research papers into testable implementations and explain technical trade-offs clearly.
• Comfortable working independently in a remote, early-stage environment.
• Interested in supporting a grant-funded prototype and willing to help define the technical scope, milestones, rates, and deliverables required for the funding application.

• Nice to have
• Experience with PPG, ECG, HRV, accelerometry, sleep modelling, wearable sensing, signal-quality estimation, uncertainty modelling, explainable AI, edge deployment, or privacy-conscious machine learning.

• What you’ll get
• You’ll own a focused biosignal-ML workstream from research and data assessment through modelling, evaluation, and technical handover. You’ll work directly with the founders and help shape the modelling architecture behind an emerging product.

• Working arrangement
• Fully remote. This is an independent-contractor engagement lasting up to four months, with a total project budget of up to CHF 20,000 depending on experience and the agreed scope. The expected start is October 2026, subject to grant approval.

The selected candidate will be presented in the funding application as an external implementation provider, with the possibility to convert to a full-time team member.