Quick overview
Job description
We're partnering with a fast-scaling MedTech company using AI to transform how one of the deadliest diseases is diagnosed and treated. Their FDA-cleared and CE-marked products are already in clinical use and deployed across multiple hospitals and health systems.
This is a strong opportunity for a machine learning engineer ready to step into a senior, delivery-focused role , with clear ownership of models running in production and room to grow as the platform scales. You will work closely with ML scientists, engineers, and product leaders to ensure AI systems are robust, reliable, and deployable in a regulated healthcare environment.
This role is hands-on and delivery-focused. It is not suitable for candidates whose experience is primarily research or data analysis without production deployment ownership in a healthcare setting.
Location and working model
Remote working in the UK is supported, with the London, Southeast, and Oxfordshire areas preferred. Hybrid working is also available. Occasional on-site collaboration is encouraged.
Key responsibilities
- Own the deployment, operation, and maintenance of machine learning models in production
- Deliver high-quality, well-tested features that directly support early detection and treatment pathways
- Collaborate with ML scientists to productionise models intended for clinical use
- Design, maintain, and improve cloud infrastructure, CI/CD pipelines, and MLOps workflows
- Monitor model performance and system health, troubleshooting and resolving production issues
- Introduce pragmatic new technologies that improve reliability, scalability, or efficiency
- At least 3 years' experience building and deploying ML systems into production environments
- Strong Python skills and hands-on experience with modern ML frameworks
- Comfortable packaging, deploying, and supporting ML models using Docker and cloud infrastructure
- Clear communicator who can work effectively across engineering, ML, and product teams
- Proactive problem-solver who takes ownership in complex production settings
- Background in healthcare and specifically medical imaging
- Experience with cloud platforms such as AWS or Azure, including infrastructure as code
- Familiarity with Kubernetes, Linux, CI/CD, data pipelines, and MLOps tooling
- Exposure to health data standards such as HL7 or FHIR
- Experience scaling ML systems or operating them under real-world constraints
What’s on offer
- Competitive compensation
- Clear scope for progression as ownership and impact grow
- Strong benefits package
- High-visibility role in a mission-led company where performance is recognised
- The opportunity to work on AI systems that have real, measurable patient impact
If you are looking for a senior, hands-on ML role where your work is used in real clinical settings and where you can grow with a purpose-driven company, we would love to hear from you.
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