Machine Learning Engineering Lead

Foundation Health
Manchester
1 month ago
Applications closed

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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.


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