Senior ML Engineer

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Senior ML Engineer (LLM & GenAI)
UK Remote | Outside IR35
Day Rate: £550-£600 per day
6-Months
This is an opportunity to join an innovative healthcare technology business on a greenfield GenAI and LLM Engineering programme. You’ll play a key role in building production-grade AI systems that support clinical and research workflows, working on LLM observability, RAG pipelines, evaluation frameworks, and scalable ML platforms within a highly data-driven environment.
The Company
They are a fast-growing healthcare technology organisation using advanced machine learning, proprietary data, and AI-driven products to improve preventative healthcare and research outcomes. Their multidisciplinary teams work across machine learning, software engineering, clinical science, and product development to deliver innovative solutions at scale. Operating in a regulated environment, they are investing heavily in the next generation of GenAI capabilities and production ML infrastructure.
The Role and Deliverables

• Build and productionise LLM, GenAI, and RAG-based applications using proprietary healthcare and research datasets.
• Develop observability and monitoring frameworks covering prompts, inference quality, latency, cost, and model performance.
• Create robust evaluation frameworks combining automated scoring, LLM-as-a-judge approaches, and human feedback loops.
• Deliver production-ready RAG and agentic AI workflows with version control, testing, deployment, and rollback capabilities.
• Partner with MLOps, Data Science, and Research teams to ensure AI systems are scalable, reliable, and compliant.
• Contribute to AI platform strategy, including model serving architecture, infrastructure decisions, and GPU utilisation.

Your Skills & Experience

• Strong experience building and deploying production machine learning systems within healthcare, life sciences, biotech, pharma, or bioresearch environments.
• Hands-on experience developing LLM, GenAI, RAG, or agent-based applications.
• Strong Python engineering skills with experience using PyTorch and modern ML tooling.
• Experience with LangChain, LangGraph, LlamaIndex, DSPy, or similar LLM orchestration frameworks.
• Strong MLOps experience including MLflow, model versioning, experiment tracking, monitoring, and production deployment.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Databricks Vector Search.
• Cloud experience across AWS, Azure, or GCP, alongside containerisation and orchestration technologies including Docker and Kubernetes.
• Familiarity with Infrastructure as Code tools such as Terraform.
• Experience operating machine learning solutions within regulated or research-led environments.

How to Apply
If you have a proven track record delivering production LLM and GenAI solutions within healthcare, biotech, or research environments, please apply with your latest CV.

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