Machine Learning Engineer
Listed on 2026-02-11
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Senior GenAI Engineer - Health Tech | Oxford (Hybrid x2 days per week)
We’re partnering with a scaling Health Tech 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.
The opportunityYou 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.
What you will be doing- 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
- 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.
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