PHARMACEUTECH R&D
AI/Machine Learning Engineer
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About Pharmaceutech
Pharmaceutech, a UK-based start-up health tech research and development company, builds technology to provide clinical teams with earlier and more objective insights into patient health. Our products, including software and medical devices, address pressing health issues and modernise real-world medicine management beyond clinical trials.
We combine biosensing, wearable hardware, and AI to turn real physiological and biochemical signals into decision support clinicians can act on, in areas of serious unmet need in healthcare. We have recently secured funding to take our lead platform from proof of concept to a clinically validated system over the next two years.
That work is OpiBud: a wearable patch for monitoring opioid use disorder and flagging early relapse or overdose risk. This role sits within a small, multidisciplinary team of engineers and scientists working together toward shared research goals. You would be contributing your expertise as part of that team, at an early and hands-on stage, on problems that do not yet have a fixed answer. All research, models, and intellectual property developed in the role belong to Pharmaceutech Ltd.
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Your responsibilities
Working with the hardware, firmware, and clinical members of the team, you will contribute to:
- Models that interpret combined biochemical and physiological signals to indicate baseline state, treatment response, behavioural instability, and early relapse or overdose risk
- The data pipeline from device to cloud to the clinician-facing dashboard
- Approaches suited to limited, early-stage data, and to small, noisy biosignal datasets
- Explainability and clinician-facing outputs, so results support a clinician's judgement rather than replacing it
- Shaping what the device captures, so the data serves the models
- Model validation and documentation appropriate to a regulated clinical context
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Qualifications
- A degree in machine learning, computer science, data science, biomedical engineering, or a related quantitative field.
- A relevant MSc or PhD, particularly in health or biosignal machine learning, is a strong advantage.
Essential experience
- Machine learning for time-series or biosignal data
- Experience with health, physiological, or other real-world sensor data
- Sound grasp of model validation, and of building models that are interpretable, not just accurate
- Ability to work end to end, from raw data pipeline through to a usable output
Highly desirable
- Awareness of machine learning in medical devices and the associated regulatory expectations
- Experience with small-data or few-shot problems rather than only large-scale datasets
- Familiarity with clinical decision-support design and clinician workflows
Salary
£40,000 fixed for the initial two-year project phase, with a planned increase after that.
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