Senior Machine Learning Engineer - Applied AI & LLMs (x/f/m)
Doctolib · Paris, Paris, France · GB
Posted 60+ days ago
Health Tech
On-site
Not yet analysed
Demand85
Career growth88
Healthcare fit25
Remote potential60
5-year outlook
Senior ML engineers in health tech typically command top-tier salaries, with strong growth potential as AI adoption in healthcare expands. Exact figures vary by location and company, but this role is likely well-compensated.
Clinical license
Not required
Applicant reach
moderate
Seniority
senior
Employment type
–
Date found
2026-09-06
Intelligence details
Why this is worth applying to
Clinicians with a strong background in machine learning and AI engineering should consider this role, as it offers the chance to directly impact patient care at scale. However, without 7+ years of ML experience, it's not a realistic entry point.
Who should apply
Clinicians who have transitioned into ML engineering with deep technical expertise, or those with a dual background in healthcare and AI/ML at a senior level.
CV angle
Emphasize any clinical domain knowledge as a differentiator for understanding patient needs, but lead with ML engineering achievements: production systems, LLM fine-tuning, retrieval pipelines, and experimentation. Frame clinical experience as domain expertise that informs product decisions.
Skills to highlight
- LLM fine-tuning
- RAG architectures
- Vector databases
- Information retrieval
- Production ML systems
- Experiment design
- Agentic AI
- Cross-functional communication
Role summary
Senior ML engineer at Doctolib building AI systems for patient solutions, including search, retrieval, and personalized care pathways, using LLMs, VLMs, and agentic AI at scale.
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