Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Healthcare systems face growing pressure to do more with limited resources. To address this, we must shift towards early detection and prevention. Sanome is one of the first class IIb certified multimodal AI Clinical Decision Support tools (EU:MDR) and has unprecedented access to multimodal data across hundreds of thousands of patients in real-time. This is a career-defining opportunity to scale from a single use case to a full platform of clinical AI models, building insights clinical teams trust to catch emerging risks early, save time, improve outcomes, and ultimately create a human digital twin.

Sanome is at a defining moment. Our platform MEMORI is regulated, embedded, and the first 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 hundreds of clinical AI models. This is a hands-on building role where you will be deeply involved in code, data, and models every week—architecting, training, and validating clinical AI yourself, while setting the technical bar through design review, code review, and mentoring.

You will design, train, and validate models across many different clinical data modalities and settings, fusing whatever the problem demands. Every clinical AI model must earn its place in a clinician's day by answering the who, what, when, and why. Done well, this means catching deterioration and risk earlier, across more of the hospital and into the community, impacting millions of patients.

Key responsibilities include:
- 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.
- Collaborate with Product and Clinical teams to prioritize development based on clinical value, data availability, and regulatory burden.
- Lead validation efforts with QARA and Clinical teams to prove each model meets its intended use and prepare models for production.
- Monitor and maintain model performance post-deployment, including drift, bias, fairness monitoring, local calibration, continual learning, and domain adaptation.
- Understand and contribute to post-market surveillance and post-market clinical follow-up obligations.
- Set the technical bar by defining architecture and modeling approaches, and raising standards through design and code reviews and mentoring.
- Represent Sanome externally as the technical voice for clinical AI through conferences, webinars, white papers, and co-authored publications, building credibility with clinicians, partners, and the wider field.

Experience
- Demonstrable experience building clinical AI within a regulated medical device context.
- Deep understanding of continuous validation across pre-, silent, and post-deployment phases.
- Startup or early-stage company experience.
- Proven track record as a hands-on builder who has taken models to production, with clear evidence of impact.
- Strong programming and algorithmic skills in Python, with experience building reusable platforms and owning MLOps including reproducible pipelines, experiment tracking, model registry, and versioning (e.g., MLflow).
- Advanced knowledge of deep learning and transformer-based architectures, including scaling and fine-tuning over large-scale data.
- Expertise in multi-modal modeling across time-series, structured and categorical data, and clinical NLP (e.g., Clinical BERT, LLM-based extraction and summarization).

About you
- Obsession with clinical utility: you want your models used at the bedside, not just admired in papers.
- Strong communication skills, able to explain modeling trade-offs to non-technical audiences and engage clinicians.
- Passionate about setting high technical standards and mentoring others.
- Bonus points for experience with survival analysis methodologies.
- Bonus points for NHS deployment or health-data-partnership experience, or working across multiple clinical settings such as ward, ICU, and community.

Qualifications
PhD or MSc in a related field, or equivalent industry experience.