Project Tricorder — Clinical Infrastructure for Field OperationsWe're looking for a hands-on engineer to build two foundations of the Tricorder product: the evaluation harness and training data pipeline behind our AI models, and a clinical knowledge base grounded in tactical combat care, SNOMED CT and ICD-10.
Care increasingly happens somewhere else - in the field, in transit, in remote and contested environments, and in the critical minutes before a patient reaches a ward.
Tricorder builds the deployable clinical infrastructure for that world: a rugged, self-contained hardware and software platform that lets clinical teams capture, monitor and act on patient data anywhere, even when the network or the grid can't be relied on.
It is a dual-use venture serving defence medical and civilian pre-hospital care.
Our prototype product is already in user testing.
Edge AI sits at the core: multimodal language models that turn video, sensor data and clinical notes into patient records, drive predictions and inform data-driven learnings across deployments.
To trust those models in the field, we need rigorous data and evaluation - that's where you come in.
What you'll doYou'll own two workstreams, working day to day with the founder and the FF build team.
Data pipeline and evaluation harnessBuild the data foundations that tell us whether our models are good enough for clinical use.
Data labelling: design labelling schemas and guidelines, set up tooling, and run labelling with clinical input, including quality checks and inter-annotator agreement.
Data processing: build reproducible pipelines to ingest, clean, de-identify and transform multimodal data (video, sensor streams, text).
Video data organisation: structure, version and catalogue video datasets so clips, annotations and metadata stay searchable and traceable.