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- Tasks: Own and deploy machine learning models that transform healthcare diagnostics.
- Company: Fast-scaling MedTech company using AI for impactful healthcare solutions.
- Benefits: Competitive pay, strong progression opportunities, and a robust benefits package.
- Why this job: Make a real difference in patient care with cutting-edge AI technology.
- Qualifications: 3+ years in ML systems, strong Python skills, and cloud experience.
- Other info: Remote work supported, with opportunities for on-site collaboration.
The predicted salary is between 48000 - 72000 £ per year.
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
Requirements:
- 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.
Senior Machine Learning Engineer in London employer: Llama Recruitment Solutions
Contact Detail:
Llama Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the MedTech space, especially those working with AI and machine learning. Attend industry meetups or webinars to connect with potential employers and get your name out there.
✨Tip Number 2
Showcase your projects! Create a portfolio that highlights your experience with deploying ML models in production. Use platforms like GitHub to share your code and demonstrate your hands-on skills, especially in healthcare settings.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and familiarising yourself with modern ML frameworks. Be ready to discuss your experience with cloud platforms and how you've tackled real-world challenges in production.
✨Tip Number 4
Apply through our website! We’re always looking for talented individuals who are passionate about making a difference in healthcare. Don’t miss out on the chance to join a mission-led company where your work can have a real impact.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with deploying ML models in production. We want to see how you've taken ownership of projects and delivered results, especially in healthcare settings.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about this role and how your skills align with our mission. Share specific examples of your work that demonstrate your hands-on experience and problem-solving abilities.
Showcase Your Technical Skills: Don’t forget to mention your strong Python skills and familiarity with cloud platforms like AWS or Azure. We’re keen to know about your experience with Docker, Kubernetes, and MLOps tooling, so make it stand out!
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 any important updates from our team!
How to prepare for a job interview at Llama Recruitment Solutions
✨Know Your Stuff
Make sure you brush up on your machine learning frameworks and deployment strategies. Be ready to discuss your hands-on experience with Python, Docker, and cloud platforms like AWS or Azure. They’ll want to see that you can not only talk the talk but also walk the walk in a production environment.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex issues in previous roles, especially in healthcare settings. Highlight your proactive approach to troubleshooting and maintaining ML models in production. This will demonstrate your ownership mentality and ability to thrive under real-world constraints.
✨Communicate Clearly
Since this role involves collaboration across various teams, practice articulating your thoughts clearly and concisely. Be ready to explain technical concepts in a way that non-technical stakeholders can understand. This will show that you can bridge the gap between engineering, ML, and product teams effectively.
✨Understand the Mission
Familiarise yourself with the company’s mission and the impact of their AI systems on patient care. Being able to connect your skills and experiences to their goals will not only impress them but also show that you’re genuinely interested in contributing to their mission-led work.
