Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy LLM-driven features for real-world healthcare applications.
- Company: A scaling HealthTech platform in Oxford with a focus on Generative AI.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by working with cutting-edge AI technologies.
- Qualifications: Strong experience with LLMs, NLP systems, and Python in production environments.
- Other info: Collaborative team environment with a focus on innovation and best practices.
The predicted salary is between 48000 - 72000 £ per year.
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.
The opportunity
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.
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
What you will need
- 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.
Machine Learning Engineer in Oxford employer: NearTech Search
Contact Detail:
NearTech Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to folks in the HealthTech space, especially those working with Generative AI. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to NLP and LLMs. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. Practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Machine Learning Engineer in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior GenAI Engineer. Highlight your experience with LLMs and NLP systems, and don’t forget to mention any relevant projects that showcase your skills in production environments.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about working at the intersection of healthcare and AI. Share specific examples of how you've tackled similar challenges in the past.
Showcase Your Technical Skills: When filling out your application, be sure to highlight your strong Python skills and any experience with cloud environments. We want to see how you’ve implemented and optimised NLP pipelines or worked with LLMs in production.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!
How to prepare for a job interview at NearTech Search
✨Know Your Stuff
Make sure you brush up on your knowledge of LLMs and NLP techniques. Be ready to discuss your experience with embeddings, transformers, and retrieval-augmented generation. The more specific examples you can provide from your past work, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled ambiguous problems in the past. Think of a few scenarios where you took ownership from problem definition to delivery, especially in regulated environments. This will demonstrate your ability to navigate complex challenges.
✨Collaborate Like a Pro
Since this role involves working closely with backend engineers and data scientists, be ready to discuss your collaborative experiences. Highlight any projects where teamwork was key to success, and how you contributed to architectural decisions.
✨Ask Smart Questions
Prepare insightful questions about the company's approach to GenAI in healthcare. This shows your genuine interest in the role and helps you understand their expectations. Ask about their current challenges or future projects related to LLMs and NLP.
