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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML LLM Engineer - **Company:** Openai Gpt - **Location:** Manchester, UK (Remote available) - **Salary:** £6,000.0 - **Contract:** Contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Fast Healthcare Interoperability Resources, Large Language Models, Model Validation, HuggingFace, Api Design, GPT, Data Generation - **Published:** August 14, 2026 - **Apply:** https://www.careerjet.co.uk/job/gb07522be000f1386c4f61aa4f559fff92/eaa ## About the Role * Production LLM fine-tuning, LoRA, QLoRA, or equivalent * AWS SageMaker, training jobs, endpoint deployment, evaluation * Synthetic data generation for model training * Understanding of NHS or healthcare AI safety constraints * Ability to enforce no real patient data in training architecturally * AWS Transcribe and ElevenLabs or equivalent STT/TTS * OpenAI API integration * Ability to evaluate model output for production readiness Useful but not essential NHS FHIR API · LangChain · RLHF · DPO · SageMaker Ground Truth · Hugging Face · DCB0129 awareness Not suitable if * You have only called LLM APIs rather than fine-tuned and deployed models * You cannot architect a patient data firewall structurally - not just as a policy * You are not comfortable owning model evaluation and sign-off independently ## Description Payment: Weekly worksheet submitted Friday · reviewed Monday · invoice paid within 7 days of acceptance What is Ladybird? A Manchester healthtech startup. Small team. Moving fast. Building inCall - an AI receptionist for NHS GP practices. Project-based engagement with option to extend. What is this role? Hands-on AI and LLM engineering. You will integrate OpenAI as an interim model from day one, then design, build, fine-tune, and deploy a LLaMA 3 8B model from scratch - replacing OpenAI in the live pipeline by end of Month 3. Two tracks running simultaneously. Requirement, read this first You must have production experience fine-tuning and deploying large language models - not just calling APIs. Track A Day one OpenAI GPT integrated into the live 3CX call pipeline via AWS Transcribe and ElevenLabs so the full voice flow is testable immediately. Track B Months 1 to 3 LLaMA 3 8B fine-tuned on 10,000+ synthetic NHS GP call examples using LoRA on SageMaker. Deployed to EC2 g4dn.xlarge. Replaces OpenAI by end of Month 3. If you have never fine-tuned a model and deployed it to a production inference endpoint, this role is not for you. What you will build OpenAI GPT integrated into live call pipeline from day one AWS Transcribe (en-GB) with custom NHS GP vocabulary ElevenLabs TTS for voice responses 10,000+ synthetic NHS GP call training dataset LLaMA 3 8B fine-tuned via LoRA on SageMaker SageMaker inference endpoint - minimum 70% accuracy on held-out test set NHS PDS FHIR API integrated for patient context (Month 3) LLaMA replaces OpenAI in live pipeline (Month 3) Safety and fallback layer implemented and documented 3-month delivery plan Month 1: OpenAI integrated into live pipeline. Full voice flow demonstrated. Synthetic dataset design approved. 1,000+ example outlines complete. Month 2: LLaMA 3 8B fine-tuned on 10,000+ examples. SageMaker endpoint live. Minimum 70% accuracy on 100-example held-out test set accepted in writing. Month 3: NHS PDS FHIR integrated. LLaMA replaces OpenAI in live pipeline. Full POC demo. All eight NHS GP call scenario types demonstrated. 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