AI Software Engineer – Project Tricorder

Founders Factory

. Build the data foundations needed to evaluate AI models for clinical use .

Posted 10/6/2026full-timeBristol • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building data foundations for AI models in clinical settings, with strong capabilities in Python, data engineering, and machine learning evaluation frameworks. Proficient in handling sensitive clinical data and familiar with NHS standards and health-tech environments.

Highest-signal resume keywords

Python ProgrammingData EngineeringMachine Learning Evaluation FrameworksNLP ExperienceClinical Terminologies Knowledge

ATS Keywords

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Hard Skills

Data LabellingData PreparationEntity ExtractionDocument ParsingData ModellingBenchmarkingVideo Data ProcessingQuality ControlAutomated Evaluation HarnessProduction Data Pipelines

Soft Skills

PragmatismSpeedCollaboration

Tools & Technologies

Annotation ToolingDatabasesFHIRHL7SNOMED CTICD-10Dm+d

Industry Keywords

Health-TechClinical InformaticsRegulated DomainEarly-Stage Startup Experience

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Build the data foundations needed to evaluate AI models for clinical use
Design labelling schemas and guidelines, set up tooling, run labelling with clinical input, and perform quality checks and inter-annotator agreement analysis
Build reproducible pipelines to ingest, clean, de-identify and transform video, sensor and text data
Structure, version and catalogue video datasets with searchable and traceable clips, annotations and metadata
Assemble balanced, documented training, validation and test datasets with lineage from raw data to model input
Build an automated evaluation harness for vision-language and NLP models
Benchmark models against clinically meaningful metrics, track regressions and support build-vs-buy decisions
Design the clinical knowledge-base schema and data store
Ingest and map TC3, SNOMED CT, ICD-10 and related NHS standards, including cross-mappings
Extract entities and relationships from clinical text and link them to coded concepts
Parse and structure PDFs, clinical notes and forms into the database
Work with clinicians to align the knowledge base with clinical reasoning and pre-hospital workflows
Deliver a working evaluation harness, labelled and versioned core dataset, and initial product-linked knowledge base within the first three months
Work day to day with the founder and FF build team

Requirements

What you’ll need

Strong Python and data engineering skills
Track record of shipping production data or ML pipelines, not just research notebooks
Hands-on experience building ML evaluation frameworks, benchmarks or test harnesses, ideally for vision, video or language models
Experience running data labelling and training-data preparation, including annotation tooling and quality control
Working knowledge of databases and data modelling
Practical NLP experience: entity extraction, entity linking or document parsing
Comfort handling sensitive data under data protection and clinical safety constraints
Pragmatism and speed, including making build-vs-buy decisions and shipping in weeks
Experience with SNOMED CT, ICD-10, dm+d or other NHS clinical terminologies and coding
Background in health-tech, clinical informatics or another regulated domain such as defence
Experience with video data at scale, including frame sampling, temporal annotation and multimodal datasets
Familiarity with FHIR or HL7 interoperability standards
Experience working with LLMs and VLMs, including edge or on-device deployment
Early-stage startup experience, especially as a founding or early engineer

Benefits

Comp & perks

Competitive day rate for consultancy agreement
Shares as part of the permanent employment package
Scope to grow into a longer-term role as the engineering team develops
Flexible consultancy agreement, rolling by mutual agreement
Permanent employment option