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For Companies At a Glance
- 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 deployment, strong Python skills, and healthcare experience.
- Other info: Remote work supported, with opportunities for hybrid 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 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
✨Tip Number 1
Network like a pro! Reach out to folks in the MedTech and AI space on LinkedIn or at industry events. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Showcase your projects! If you've got hands-on experience with ML models, make sure to have a portfolio ready. Highlight your role in deploying those models in production – that’s what they want to see!
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and ML frameworks. Be ready to discuss how you’ve tackled real-world problems in production settings – they’ll want to know you can handle the heat!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with deploying ML systems in production, especially in healthcare settings. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI in healthcare and how you can contribute to transforming patient care. Be sure to mention specific projects or technologies you've worked with that relate to the job.
Showcase Your Hands-On Experience: We’re looking for someone who’s not just about theory. In your application, emphasise your hands-on experience with Python, Docker, and cloud platforms like AWS or Azure. Let us know how you've tackled real-world challenges in ML deployment!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
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 Python skills. Be ready to discuss specific projects where you've deployed models in production, especially in healthcare settings. This will show that you have the hands-on experience they're looking for.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex production issues in the past. Highlight your proactive approach and ownership in resolving these challenges, as this role demands a strong problem-solver who can thrive under real-world constraints.
✨Communicate Clearly
Since you'll be collaborating with ML scientists, engineers, and product leaders, practice articulating your thoughts clearly. Be ready to explain technical concepts in a way that's understandable to non-technical team members, showcasing your ability to bridge gaps between teams.
✨Familiarise Yourself with Healthcare Standards
Brush up on health data standards like HL7 or FHIR, as well as cloud platforms such as AWS or Azure. Being knowledgeable about these areas will demonstrate your readiness to work in a regulated healthcare environment and your commitment to delivering high-quality, impactful solutions.
