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Sanome

Head of Clinical AI

London
Posted about 20 hours ago
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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. Leading that could be the defining moment of your career, the kind that rarely comes around.

This is a building role, not directing from a distance. You'll own clinical AI at Sanome, setting direction with the C-suite, leading a world-class team of ML engineers, and staying hands-on in the code, data, and models. 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, Commercial, and Clinical, choose what to build next, weighing clinical value, data, regulatory burden, and commercial pull.
    • With QARA and Clinical, lead validation to prove each model meets its intended use, then work with engineering to get it production-ready.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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  • 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.
  • Lead

    • You are the benchmark for the team.
    • Setting technical direction, mentoring and owning the team's delivery and growth.
  • 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.

You must apply if you

  • have start-up or early-stage experience.
  • obsess about clinical utility. You want your models used at the bedside, not admired in a paper.
  • are a hands-on builder who loves designing, training, writing the code, and validating production models.
  • have demonstrable experience building clinical AI within a regulated medical device context. Your playground is pre-/silent/post- deployments, you obsess about continuous validation and you know it’s not about AUROC on a test set and you deeply understand the interplay of intended use with model development and validation.
  • have taken models to production using engineering best practices, writing high-standard code and building reusable platforms and components, not bespoke one-offs.
  • work at peer-review level. Your quality bar is publishable rigour, even though your goal is models that clinicians trust at the bedside, not papers on a shelf.
  • have strong programming and algorithmic skills, specifically in Python or other relevant languages.
  • have advanced knowledge of deep learning and transformer-based architectures, including scaling and fine-tuning models over large-scale data sources.
  • are strong in multi-modal modelling across time-series, structured, and categorical data, and comfortable with unstructured free-text notes through clinical NLP and information extraction.
  • have experience communicating your work to a non-technical and healthcare audience.
  • are curious, hungry and constantly push the boundaries of what’s possible
  • have a PhD in a related field, or equivalent industry experience

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Bonus points if you

  • have line-management experience.
  • have advanced clinical NLP experience, such as RAG, patient summarisation, or Clinical BERT-type models.
  • have experience evaluating LLMs or generative models in sensitive or regulated settings.
  • have experience with survival analysis methodologies.
  • have NHS deployment or health-data-partnership experience.
  • have experience across more than one clinical setting, such as ward, ICU, and community.

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.

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Skills

Clinical AI
Machine Learning
Python
Deep Learning
Transformer Architectures
Multi-modal Modelling
Clinical NLP
Medical Device Regulation
Model Validation
Production Engineering
Survival Analysis
LLM Evaluation
RAG
Clinical Decision Support
Data Science
Team Leadership

Location

London, England, United Kingdom

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