Healthcare systems face growing pressure to do more with limited resources. To address this, we must shift towards early detection and prevention.We are one of the first class IIb certified multimodal AI Clinical Decision Support tools (EU:MDR) and have unprecedented access to multimodal data across hundreds of thousands of patients in real-time. This is a career-defining opportunity. You'll scale us from a single use case to a full platform of clinical AI models, building the insights clinical teams trust to catch emerging risks early, save time, improve outcomes, and ultimately a human digital twin. About the roleSanome is at a defining moment, our platform MEMORI is regulated, embedded and the 1st use case (predicting infections and downstream complications like sepsis) is live in clinical practice. The opportunity now is to scale this into a clinical intelligence platform with 100s of clinical AI models.This is a hands-on building role. You'll be in the code, data and models every week — architecting, training and validating clinical AI yourself, and setting the technical bar for how it is built here through design review, code review and mentoring. You'll design, train, and validate across many different clinical data modalities and settings fusing whatever the problem demands.Every clinical AI model has to earn its place in a clinician's day, answering the who, what, when and why. Done well, that means catching deterioration and risk earlier, across more of the hospital and into the community, for millions of patients. What you will doBuild and own the platform - Design, train, and validate production clinical AI across the portfolio. Own the reusable, multi-modal infrastructure and explainability layer that ships fast and safely. With Product and Clinical, choose what to build next, weighing clinical value, data, and regulatory burden. With QARA and Clinical, lead validation to prove each model meets its intended use, then work with engineering to get it production-ready.Monitor and maintain - Own model performance once deployed. Drift, bias and fairness monitoring, local calibration, continual learning and domain adaptation. Understand how this feeds our PMS/PMCF obligations and think about PCCP.Set the technical bar - You are the benchmark for how clinical AI is built here. Setting technical direction, making the calls on architecture and modelling approach, and raising the standard through design review, code review and mentoring. Communicate and represent - Be Sanome's technical voice for clinical AI externally, through conferences, webinars, white papers, and co-authored publications, building our credibility with clinicians, partners, and the wider field.RequirementsYou must apply if youhave demonstrable experience building clinical AI within a regulated medical device context. You obsess about continuous validation across pre-, silent and post-deployment, you know it’s not about AUROC on a test set, and you deeply understand how intended use shapes model development and validation.have startup experience or experience of working in an early-stage companyare a hands-on builder who has taken models to production and can evidence it. Tell us what you shipped, who used it, and what happened to it after launch.are a strong engineer with strong programming and algorithmic skills in Python. You write high-standard code, build reusable platforms rather than bespoke one-offs, and own the MLOps around them – reproducible pipelines, experiment tracking, model registry and versioning, with tools such as MLflow.obsess about clinical utility. You want your models used at the bedside, not admired in a paper.have advanced knowledge of deep learning and transformer-based architectures, including scaling and fine-tuning over large-scale data, and are strong in multi-modal modelling across time-series, structured and categorical data, including free-text notes through clinical NLP (such as Clinical BERT-type models and LLM-based extraction and summarisation of clinical narrative).have a PhD / MSc in a related field, or equivalent industry experience Bonus points if youcommunicate well. You can hold a room of clinicians and explain a modelling trade-off to a non-technical audience.have experience with survival analysis methodologies.have NHS deployment or health-data-partnership experience, or have worked across more than one clinical setting such as ward, ICU and community.BenefitsCompetitive salary, meaningful EMI options with real upside, private healthcare, and more. The real reason you want to work here is to make a difference and be part of something that will positively impact millions of people worldwide.
Healthcare systems face growing pressure to do more with limited resources. To address this, we must shift towards early detection and prevention.
We are one of the first class IIb certified multimodal AI Clinical Decision Support tools (EU:MDR) and have unprecedented access to multimodal data across hundreds of thousands of patients in real-time.
This is a career-defining opportunity. You'll scale us from a single use case to a full platform of clinical AI models, building the insights clinical teams trust to catch emerging risks early, save time, improve outcomes, and ultimately a human digital twin.
About the role
Sanome is at a defining moment, our platform MEMORI is regulated, embedded and the 1st use case (predicting infections and downstream complications like sepsis) is live in clinical practice. The opportunity now is to scale this into a clinical intelligence platform with 100s of clinical AI models.
This is a hands-on building role. You'll be in the code, data and models every week — architecting, training and validating clinical AI yourself, and setting the technical bar for how it is built here through design review, code review and mentoring. You'll design, train, and validate across many different clinical data modalities and settings fusing whatever the problem demands.
Every clinical AI model has to earn its place in a clinician's day, answering the who, what, when and why. Done well, that means catching deterioration and risk earlier, across more of the hospital and into the community, for millions of patients.
What you will do
Build and own the platform - Design, train, and validate production clinical AI across the portfolio. Own the reusable, multi-modal infrastructure and explainability layer that ships fast and safely. With Product and Clinical, choose what to build next, weighing clinical value, data, and regulatory burden. With QARA and Clinical, lead validation to prove each model meets its intended use, then work with engineering to get it production-ready.
Monitor and maintain - Own model performance once deployed. Drift, bias and fairness monitoring, local calibration, continual learning and domain adaptation. Understand how this feeds our PMS/PMCF obligations and think about PCCP.
Set the technical bar - You are the benchmark for how clinical AI is built here. Setting technical direction, making the calls on architecture and modelling approach, and raising the standard through design review, code review and mentoring.
Communicate and represent - Be Sanome's technical voice for clinical AI externally, through conferences, webinars, white papers, and co-authored publications, building our credibility with clinicians, partners, and the wider field.
Requirements
You must apply if you
- have demonstrable experience building clinical AI within a regulated medical device context. You obsess about continuous validation across pre-, silent and post-deployment, you know it’s not about AUROC on a test set, and you deeply understand how intended use shapes model development and validation.
- have startup experience or experience of working in an early-stage company
- are a hands-on builder who has taken models to production and can evidence it. Tell us what you shipped, who used it, and what happened to it after launch.
- are a strong engineer with strong programming and algorithmic skills in Python. You write high-standard code, build reusable platforms rather than bespoke one-offs, and own the MLOps around them – reproducible pipelines, experiment tracking, model registry and versioning, with tools such as MLflow.
- obsess about clinical utility. You want your models used at the bedside, not admired in a paper.
- have advanced knowledge of deep learning and transformer-based architectures, including scaling and fine-tuning over large-scale data, and are strong in multi-modal modelling across time-series, structured and categorical data, including free-text notes through clinical NLP (such as Clinical BERT-type models and LLM-based extraction and summarisation of clinical narrative).
- have a PhD / MSc in a related field, or equivalent industry experience
Bonus points if you
- communicate well. You can hold a room of clinicians and explain a modelling trade-off to a non-technical audience.
- have experience with survival analysis methodologies.
- have NHS deployment or health-data-partnership experience, or have worked across more than one clinical setting such as ward, ICU and community.
Benefits
Competitive salary, meaningful EMI options with real upside, private healthcare, and more. The real reason you want to work here is to make a difference and be part of something that will positively impact millions of people worldwide.
At Sanome, we believe healthcare can and should be better.Today’s healthcare systems are reactive and overburdened, placing both patients and providers at risk. The path forward lies in prevention-detecting health changes at the earliest possible stage.This is why we are developing a solution designed to predict emerging risks in patients. By integrating and analysing existing data, we generate actionable clinical insights to support faster, more informed decision-making, all within the framework of a regulated Software-as-a-Medical Device (SaMD).Find out how our unique approach seeks to improve patient outcomes and provide clinicians the insights they need to act earlier.
At Sanome, we believe healthcare can and should be better.
Today’s healthcare systems are reactive and overburdened, placing both patients and providers at risk. The path forward lies in prevention-detecting health changes at the earliest possible stage.
This is why we are developing a solution designed to predict emerging risks in patients. By integrating and analysing existing data, we generate actionable clinical insights to support faster, more informed decision-making, all within the framework of a regulated Software-as-a-Medical Device (SaMD).
Find out how our unique approach seeks to improve patient outcomes and provide clinicians the insights they need to act earlier.
