AI Native Engineer: LLM-Driven Diagnostic Pipelines (Hybrid)

AI Native Engineer: LLM-Driven Diagnostic Pipelines (Hybrid)

Full-Time 70000 - 90000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and maintain AI-driven pipelines for extracting clinical data from pathology reports.
  • Company: Join Unilabs, a leader in innovative healthcare technology.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Be part of a dynamic team focused on improving patient outcomes.
  • Why this job: Make a real difference in healthcare by working with cutting-edge AI technologies.
  • Qualifications: Experience in AI/ML engineering and backend development is essential.

The predicted salary is between 70000 - 90000 Β£ per year.

Unilabs is seeking a backend-focused AI/ML engineer to design and maintain LLM-based extraction pipelines for pathology reports. You will extract clinical entities and biomarkers, integrate data across LIS and molecular systems, and ensure compliant, high-quality data delivery.

The role involves:

  • Evaluating orchestration frameworks
  • Building confidence scoring
  • Implementing robust APIs with HL7 interfaces in a regulated healthcare context

AI Native Engineer: LLM-Driven Diagnostic Pipelines (Hybrid) employer: Unilabs Group

Unilabs is an exceptional employer, offering a dynamic and entrepreneurial work environment where innovation thrives. As a Director of Biopharma Partnerships, you will benefit from a hybrid working model, competitive compensation, and the opportunity to take long-term ownership of a strategic healthcare product. With a focus on collaboration and employee growth, Unilabs empowers its team members to make a meaningful impact in the diagnostics field while leveraging Europe's largest multi-modal diagnostic pool.

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Contact Details:

Unilabs Group Recruitment Team

We think you need these skills to ace AI Native Engineer: LLM-Driven Diagnostic Pipelines (Hybrid)

Backend Development
AI/ML Engineering
LLM-based Extraction Pipelines
Clinical Entity Extraction
Data Integration
LIS and Molecular Systems
Data Compliance