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AI ENGINEER – COMPUTER VISION & DEEP LEARNING FOR DIGITAL PATHOLOGY
France
· Full-time
·
Entry
Descriptif du poste
Location: Paris (Station F) – Hybrid
Contract: Full-time
Salary: €3,300 – €4,100 gross/month
About RainPath
RainPath is reinventing how we diagnose human tissue.
Today, pathology still relies on chemical stains, manual processing, and long delays to detect diseases. We’re building the first 100% software-based diagnostic platform — using deep learning and advanced imaging to detect lesions and biomarkers directly from raw slides.
We Combine Two Major Innovations
The Role – AI Engineer (Computer Vision)
You’ll join our core R&D team and contribute to the development of AI models that power the most advanced digital pathology workflows to date.
You’ll be working with real medical datasets (WSI, autofluorescence, hyperspectral), help train and evaluate models for classification, segmentation, and virtual staining — and turn those models into product-grade tools for real pathologists.
You’ll also contribute to the exploration of new imaging modalities (e.g. autofluorescence, hyperspectral, Raman) by helping process, align, and exploit raw optical signals within our training pipelines.
You’ll be working directly with the CTO, and collaborate closely with medical experts.
What You’ll Do
Who You Are
Hiring Process
At RainPath, we value kindness, honesty, and inclusivity. We strongly believe that diverse teams build better products — and we’re committed to creating a safe and empowering environment for everyone, regardless of background, gender, ethnicity, or orientation.
How To Apply
Complete your application on the website with your resume.
No formal letter needed — just a few words about why this internship (or AI in healthcare) excites you.
Informations complémentaires
Location: Paris (Station F) – Hybrid
Contract: Full-time
Salary: €3,300 – €4,100 gross/month
About RainPath
RainPath is reinventing how we diagnose human tissue.
Today, pathology still relies on chemical stains, manual processing, and long delays to detect diseases. We’re building the first 100% software-based diagnostic platform — using deep learning and advanced imaging to detect lesions and biomarkers directly from raw slides.
We Combine Two Major Innovations
- A virtual staining & biomarker detection module, trained on real clinical data
- A workflow automation module, handling pre-screening, structured reporting, and traceability
- Instant diagnostics
- 100× cheaper workflows
- A fully digital, scalable diagnostic pipeline
The Role – AI Engineer (Computer Vision)
You’ll join our core R&D team and contribute to the development of AI models that power the most advanced digital pathology workflows to date.
You’ll be working with real medical datasets (WSI, autofluorescence, hyperspectral), help train and evaluate models for classification, segmentation, and virtual staining — and turn those models into product-grade tools for real pathologists.
You’ll also contribute to the exploration of new imaging modalities (e.g. autofluorescence, hyperspectral, Raman) by helping process, align, and exploit raw optical signals within our training pipelines.
You’ll be working directly with the CTO, and collaborate closely with medical experts.
What You’ll Do
- Train and fine-tune deep learning models (GANs, U-Nets, encoders...)
- Design experiments for tissue classification & virtual staining
- Preprocess and manage medical imaging datasets (tiles, annotations, WSI...)
- Evaluate model performance using clinical and statistical metrics
- Build reproducible pipelines (data loaders, training loops, experiment tracking)
- Integrate models into the RainPath platform
- Stay up to date with recent CV/ML research and contribute to internal R&D
- Languages: Python
- Frameworks: PyTorch, PyTorch Lightning, FastAPI
- Tools: Git, GitHub, Docker, W&B, Hugging Face
- Data: WSI, patches, autofluorescence, paired IHC
- A hands-on role at the heart of a deeptech project
- Mentorship and technical guidance from experienced founders
- Access to real-world clinical datasets & product context
- A hybrid work culture with 1 offsite week/month in coliving
- The chance to build something that truly matters — for patients, doctors, and science
Who You Are
- Graduate in computer science, AI, applied math, or biomedical engineering
- Strong skills in Python and deep learning, especially with computer vision models
- Experience with image-based datasets, training pipelines, and evaluation strategies
- Curious, fast learner, and excited by real-world impact
- Comfortable with Git and collaborative coding practices
- Hands-on experience with GANs or transformers
- Knowledge of medical imaging or histopathology
- Familiarity with MLOps tools (W&B, DVC, Docker…)
- Exposure to spectral data or multi-channel imaging
- Interest in healthcare and ethical, responsible AI
Hiring Process
- 30-min intro chat with CEO
- 30-min tiny project presentation with CTO
- 30-min in-person peer-coding with CTO
- → Quick feedback & offer within days
At RainPath, we value kindness, honesty, and inclusivity. We strongly believe that diverse teams build better products — and we’re committed to creating a safe and empowering environment for everyone, regardless of background, gender, ethnicity, or orientation.
How To Apply
Complete your application on the website with your resume.
No formal letter needed — just a few words about why this internship (or AI in healthcare) excites you.
Informations complémentaires
- Type de contrat : CDI
- Lieu : Paris
- Télétravail partiel possible
- Salaire : entre 3300€ et 4100€ / mois
Key Skills
Ranked by relevance
ai
deep learning
pytorch
git
computer vision
python
docker
mlops
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- Posted
- Aug 24, 2025
- Type
- Full-time
- Level
- Entry
- Location
- Paris
- Company
- STATION F
Industries
Technology
Information
Internet
Categories
Engineering
Information Technology
Related Jobs
3 roles aligned with this opportunity
View Job Details
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DEEP LEARNING ENGINEER - VISION & R&T
2026-05-14
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Engineering
View Job Details
Related
AI SOFTWARE ENGINEER
2026-05-07
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View Job Details
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DÉVELOPPEUR BACK-END .NET / C#
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