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Tricorder Systems

AI Software Engineer

Bristol, UK
MedTech
Tricorder is building a world where patients receive the right care, at the right time, wherever crisis strikes. Offline first edge compute delivers world class care anywhere in the world within 24hrs
Active
13 hours ago
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Skills & Experience

Job roles: AI Engineer, Data Scientist, Machine Learning Engineer
Experience level: Junior, Mid, Senior
Core skills considered: Artificial Intelligence
Other skills considered: NLP, Machine Learning, Data Modeling, Computer Vision

Logistics

Base salary: £30K - £150K   ·   0.5% - 3% Equity
Employment type: Permanent
Remote working: Hybrid (up to 4 remote days p/w)
Visa sponsorship: Not available
Security clearance: SC (Security Check), or eligible and willing to be cleared

Job Description

We'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.

Most healthcare technology assumes a hospital: reliable power, connectivity and a clinician at a desk. 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 do

You'll own two workstreams, working day to day with the founder and the FF build team.

1. Data pipeline and evaluation harness

Build 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.

  • Training dataset preparation:assemble balanced, well-documented train, validation and test splits, with clear lineage from raw data to model input.

  • Eval harness:build an automated harness that benchmarks vision-language and NLP models against clinically meaningful metrics, tracks regressions and supports build-vs-buy model decisions.

2. Clinical knowledge base

Build the structured clinical knowledge base that turns unstructured input into coded, interoperable records.

  • Database design:design the schema and stand up the data store for clinical concepts and their relationships.

  • Clinical terminologies:ingest and map TC3, SNOMED CT, ICD-10 and related NHS standards, including cross-mappings between them.

  • Natural language processing:extract entities and relationships from clinical text and link them to coded concepts.

  • Document handling:parse and structure clinical documents (PDFs, notes, forms) into the database.

  • Clinical knowledge:work with clinicians to make sure the database reflects real-world clinical reasoning and pre-hospital workflows.

By the end of the first 3 months, we'd expect a working eval harness in use for model decisions, a labelled and versioned core dataset, and a first version of the knowledge base linked to the product.

What we're looking for

We don't expect one person to be expert in everything below. Strong candidates will be deep in one workstream and credible in the other.

Must-haves
  • Strong Python and data engineering skills, with a 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: you can work with ambiguity, make good build-vs-buy calls and ship in weeks, not quarters.

Nice to have
  • Experience with SNOMED CT, ICD-10, dm+d or other NHS clinical terminologies and coding.

  • A background in health-tech, clinical informatics or another regulated domain such as defence.

  • Experience with video data at scale (frame sampling, temporal annotation, 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.

Probably not the right fit if
  • You need detailed specs and a large team around you to be effective.

  • You prefer pure research over building tools people use every day.

This is a high urgency opening, and we are flexible to consider applicants either on a more flexible consultancy agreement (rolling by mutual agreement, with a competitive day rate); or a long term permanent employment contract with shares as part of the package and scope to grow into a longer-term role as Tricorder builds its engineering team.

Interview Process

  • Initial screening interview
  • Technical take home task
  • Task follow up interview
  • Final interview

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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