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- Tasks: Design and deploy cutting-edge AI models for medical imaging that improve patient care.
- Company: Join a specialised team at the forefront of healthcare technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborate with experts and influence the direction of innovative AI solutions.
- Why this job: Make a real difference in healthcare by shaping the future of clinical diagnostics.
- Qualifications: Master's or PhD in ML/AI, with 5+ years in ML engineering and medical imaging experience.
The predicted salary is between 60000 - 80000 £ per year.
This is a unique opportunity for an experienced ML engineer to join a specialised team building AI-powered clinical systems for a range of healthcare clients. You will work at the cutting edge of medical imaging and deep learning, developing models that have a direct and meaningful impact on patient care.
If you have a strong background in computer vision with hands-on experience in medical imaging pipelines, this role was written for you.
- Design, train, and deploy production-grade deep learning models applied to medical imaging data.
- This is a hands-on engineering role with significant ownership and influence over how AI shapes the future of clinical diagnostics.
- You will work closely with scientific and clinical stakeholders to translate complex medical problems into robust, scalable ML solutions and help define the technical direction of the team.
Qualifications:
- Master's or PhD in Machine Learning, AI, or Computer Science
- ~5+ years of senior ML engineering experience
- ~Proven experience in medical imaging or computer vision
- ~Experience building agentic AI systems with LangChain and RAG pipelines
AWS Engineer (Python) employer: Platform Recruitment
Contact Detail:
Platform Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Engineer (Python)
✨Tip Number 1
Network like a pro! Reach out to professionals in the healthcare AI space on LinkedIn or at industry events. We can’t stress enough how personal connections can open doors to opportunities that aren’t even advertised.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those related to medical imaging and deep learning. We recommend using GitHub to share your code and demonstrate your expertise in building production-grade models.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. We suggest doing mock interviews with friends or using platforms that simulate real interview scenarios to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace AWS Engineer (Python)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in ML engineering and medical imaging. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in healthcare and how your background makes you the perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool projects related to deep learning or medical imaging, make sure to mention them! We love seeing practical examples of your work that demonstrate your expertise and creativity.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves!
How to prepare for a job interview at Platform Recruitment
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning, especially in medical imaging and computer vision. Be ready to discuss specific projects you've worked on and the impact they had. This shows you're not just familiar with the theory but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex medical problems in the past. Think of examples where you translated a challenging issue into a scalable ML solution. This will demonstrate your ability to think critically and creatively, which is crucial for this role.
✨Engage with Stakeholders
Since you'll be working closely with scientific and clinical stakeholders, practice how you would communicate technical concepts to non-technical audiences. Being able to bridge that gap is key, so think of ways to explain your work in simple terms.
✨Be Ready for Technical Questions
Expect some deep dives into your technical expertise, especially around LangChain and RAG pipelines. Brush up on these technologies and be prepared to discuss how you've used them in your previous roles. Confidence in your technical skills will go a long way!