Descriptif du poste
Full-Time (Permanent Contract)
Location: Paris (Station F)
Salary: Competitive, based on profile and experience + equity
About RainPath
We are shifting from chemical tissue analysis on biopsies to AI-enhanced virtual analysis. This approach is less costly, faster, and, above all, more accurate. It is a revolution that could transform diagnostics worldwide.
To support the development of this technology, RainPath is building a purpose-driven software for pathologists.
We work with large, high-quality datasets and have a reliable data acquisition pipeline through clinical partners. Our focus is twofold: develop a disruptive virtual staining technology, and ship practical software that accelerates workflows and improves pathologists’ day-to-day experience. Several modules are already in production with pilot customers.
RainPath is an ambitious healthtech startup with a strong vision, real-world impact, and a determined team.
The Role
- Design, train, and deploy models for classification, segmentation, virtual staining, and biomarker detection on whole-slide images
- Own data pipelines for curation, preprocessing, tiling, and evaluation, with strong experiment tracking and reproducibility
- Turn research into production services using robust MLOps practices, including containerization, CI, monitoring, and rollback strategies
- Integrate models into the platform in close collaboration with product and fullstack teams, contribute to APIs and service layers when needed
- Validate performance with clinically meaningful metrics, write clear documentation, and contribute to internal technical notes
- Read, reproduce, and adapt state-of-the-art ideas where they add value, in dialogue with external labs and domain experts
- Help debug live systems, reduce latency and cost, and improve reliability and observability over time
- Mentor engineers and interns, set high standards for code quality, testing, and review