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- Tasks: Design and operate cutting-edge ML systems for healthcare professionals.
- Company: Foundation Health, a rapidly growing tech company in healthcare.
- Benefits: Stock options, life assurance, virtual GP access, and 25 days paid leave.
- Why this job: Make a real impact in healthcare with innovative ML solutions.
- Qualifications: Strong Python skills and hands-on experience with LLM frameworks required.
- Other info: Join a dynamic team with hybrid working options and excellent career growth.
The predicted salary is between 48000 - 84000 £ per year.
Foundation Health powers major healthcare organisations - automating pharmacy communications, supporting patients on complex therapies and removing friction from critical healthcare workflows. Our platform is live, trusted and growing. After raising $20m at Series A, we’re accelerating product development and expanding our ML capabilities.
The Role: You’ll help define and build our production LLM systems, used directly by healthcare professionals and enterprise customers. This is not a research role - you’ll design, ship and operate ML systems that run reliably in a regulated environment. You’ll work closely with product and platform engineers, building architectural and model decisions whilst establishing best practices for evaluation, safety, observability and privacy. Over time, you’ll help shape and mentor a small ML team.
We’re looking for someone with strong software instincts, real production ML experience - who can bring good judgment around speed, quality and risk.
What You’ll Do:
- Design and operate customer-facing LLM systems in production
- Own the full ML lifecycle: model selection, evaluation, deployment, and iteration
- Build and improve RAG pipelines for real-world healthcare workflows
- Implement guardrails and safeguards, including PHI-sensitive protections
- Make informed decisions across open-source vs proprietary models, cost, latency, and quality
What We’re Looking For:
- Strong Python skills and hands-on experience with modern LLM frameworks
- Experience adapting or fine-tuning models using LoRA or equivalent techniques
- Proven experience evaluating models and using those insights to improve output
- Experience deploying models that power real products (B2B or consumer), not just internal tooling
- Good instincts for choosing the right model and switching as better options emerge, backed by clear measurements
- Deep familiarity with the open-source LLM ecosystem (e.g. Hugging Face)
- Practical experience with RAG systems
- Experience building or operating LLM safeguards, ideally in regulated or privacy-sensitive domains
What You’ll Get:
- Stock Options
- Group Life Assurance (via Legal & General), including: Death in Service Benefit (4x salary)
- Virtual GP access
- Care Concierge
- Employee Assistance Programme
- Auto-enrolment in the company pension scheme
- 25 days of paid annual leave plus bank holidays
- WeWork office in Manchester and London
- Hybrid flexible working arrangements
Interested? Hit apply, or drop a message to our Recruiter for a chat. Don’t worry if your CV isn’t up to date - we’ll cross that bridge later.
Machine Learning Engineering Lead in Manchester employer: Foundation Health
Contact Detail:
Foundation Health Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Lead in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that relate to healthcare. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for interviews by brushing up on common ML scenarios and case studies. Be ready to discuss your past experiences and how they align with the role at Foundation Health. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Foundation Health.
We think you need these skills to ace Machine Learning Engineering Lead in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Machine Learning Engineering Lead role. Highlight your Python skills and any hands-on experience with LLM frameworks, as these are key for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about healthcare and machine learning. Share specific examples of how you've designed and operated ML systems in production, as this will resonate with our mission.
Showcase Your Projects: If you’ve worked on relevant projects, don’t hold back! Include links or descriptions of your work with RAG systems or any models you've deployed. This gives us a clear picture of your capabilities.
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Foundation Health
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around LLM frameworks and RAG systems. Be ready to discuss your hands-on experience with Python and how you've deployed models in real-world scenarios. This is your chance to showcase your technical skills!
✨Understand the Company’s Mission
Foundation Health is all about improving healthcare workflows. Familiarise yourself with their platform and think about how your experience aligns with their goals. Being able to articulate how you can contribute to their mission will definitely impress the interviewers.
✨Prepare for Scenario Questions
Expect questions that ask you to solve problems or make decisions based on hypothetical situations. Think about past experiences where you had to evaluate models or implement safeguards. Use the STAR method (Situation, Task, Action, Result) to structure your answers clearly.
✨Show Your Leadership Skills
Since you'll be mentoring a small ML team, be prepared to discuss your leadership style and how you've guided others in the past. Share examples of how you've established best practices or improved team performance, as this will highlight your ability to lead effectively.
