About the role
About Tortus AI At Tortus we work with clinicians and hospitals to provide clinically safe and reliable AI. We use speech-to-text and LLM models to infer information about a patient visit and provide verified documentation and actions — eliminating the documentation burden that costs clinicians hours every day. We've recorded over 1 million consultations. Clients include London Ambulance Service and a large proportion of UK GP surgeries. We are now entering our next phase: an AI doctor product and a ~£30M Series A raise.
About
the role Senior research leadership at the intersection of product and science. You will define the AI research agenda, engage deeply with product on architectural choices, propose enhancements grounded in research, and technically guide the product engineering function in implementing those changes. You will also represent Tortus externally through publications and thought leadership — strengthening our credibility as a serious AI company operating in a high-stakes clinical domain.
What you'll do Define and lead the AI research agenda: clinical trust, safety, evidence-based AI, non-deterministic system design Partner with product on architectural decisions — bringing a research perspective to shape the approaches we choose, not just validate them after the fact Propose enhancements to existing architectures and technically guide product engineers in implementing them Publish original research; contribute to the clinical AI academic community Represent Tortus at conferences and with clinical and regulatory stakeholders Contribute to our Class IIa medical device submission Set the technical bar for AI hiring as
the team scales
What we're looking for Strong research track record: publications, patents, or equivalent in uncertainty quantification, evidential deep learning, multi-agent systems, clinical NLP, or trust modelling Track record working at the research/product interface — you can engage credibly with engineering teams and influence implementation without owning it Experience reasoning about non-deterministic systems and building defensively against model failure Comfortable in a fast-moving, commercial healthtech environment