AI Trainer (Conversational AI/LLM Optimisation)

IT Talent Solutions; London; Remote; GBP 60,000 - 80,000; Full time

Job summary

Join a forward-thinking company as you help a major healthcare client launch a WhatsApp-based AI chatbot. This remote contract role involves curating chat data, fine-tuning large language models, and ensuring compliance with healthcare standards. You'll collaborate with development teams to implement responsible AI practices while steering the continual learning loop for the chatbot. If you're passionate about AI and healthcare, this is an exciting opportunity to make a real impact in the industry.

Qualifications

• Hands-on experience with fine-tuning LLMs and prompt-engineering.
• Strong knowledge of Azure ML and cloud ML stacks.

Responsibilities

• Curate and augment chat data for fine-tuning AI models.
• Design evaluation experiments and optimize model prompts.

Skills

Fine-tuning of LLMs

Prompt-engineering in Python

Azure ML

Cognitive Services

Data labelling tooling

Statistical testing

Experiment design

Tools

Label'studio

Prodigy

Scale

MLflow

Azure ML

Job description

Remote contract Outside IR per day Initial 6-month term with planned extension to 12 months

Project snapshot
Help a major healthcare client launch a WhatsApp-based AI chatbot hosted on Microsoft Azure. You'll steer the continual learning loop that keeps the bot accurate, safe, and clinically relevant.

Key responsibilities
. Curate, label and augment real chat data to fine-tune a large-language-model (Azure OpenAI, Hugging Face, etc.)
. Design and run evaluation experiments (precision/recall, BLEU, CSAT, etc.), then turn findings into actionable model tweaks.
. Optimise prompts, retrieval-augmented-generation (RAG) chains and guard-rails to meet healthcare compliance standards (GDPR, ISO 27001, NHS DSPT).
. Define a repeatable training pipeline (MLflow or Azure ML) and performance dashboards for business stakeholders.
. Champion Responsible-AI best practice - bias checks, explainability, audit logs and drift monitoring.
. Work hand-in-hand with the chatbot dev team on release cadences and incident response.

Essential skills

• Hands-on fine-tuning of LLMs and prompt-engineering in Python.

• Azure ML, Cognitive Services, or comparable cloud ML stack.

• Data labelling tooling (Label'studio, Prodigy, Scale, or similar).

• Statistical testing, experiment design and curation of training corpora.

Desirable

• Experience with healthcare vocabularies (SNOMED, FHIR) or NHS IG.

• Familiarity with WhatsApp Business API