Machine Learning Engineer

We’re partnering with a scaling HealthTech platform based in Oxford that’s embedding Generative AI directly into core clinical and operational workflows. This is not an innovation lab or a PoC exercise. The work sits in production and supports real users in regulated healthcare environments.

They are now looking to hire a Senior GenAI Engineer to take technical ownership of LLM-powered capabilities across the product.

You will work at the intersection of NLP, large language models, and real-world healthcare data. You’ll collaborate closely with backend engineers, data scientists, and product team to design, build, and reinforce GenAI systems that ship and are maintained long-term.

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• Designing and deploying LLM-driven features for text understanding, summarisation, classification, extraction, and decision support
  
• Building and maintaining NLP pipelines across structured and unstructured clinical or operational text
  
• Implementing and optimising retrieval-augmented generation architectures, prompt strategies, and evaluation approaches
  
• Working with both open-source and hosted LLMs and integrating them into production APIs
  
• Partnering with engineering teams to ensure solutions are scalable, observable, secure, and cost-aware
  
• Contributing to architectural decisions around model choice, inference, latency, and data governance
  
• Helping establish internal best practices for GenAI reliability, testing, and iteration
  

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• Strong commercial experience working with LLMs and NLP systems in production
  
• A solid grounding in modern NLP techniques including embeddings, transformers, retrieval, fine-tuning, and evaluation
  
• Strong Python skills and experience with production-grade ML or AI engineering practices
  
• Comfort operating in ambiguous problem spaces and taking ownership from problem definition through to delivery
  
• Experience working in cloud environments and with modern data or ML tooling
  
• A pragmatic, engineering-led mindset focused on outcomes rather than hype
  

Healthcare experience is not essential. However, experience working in heavily regulated, high-accountability environments such as healthcare, life sciences, fintech, or other regulated domains would be highly beneficial.

Unfortunately, this role cannot offer visa / sponsorship.