🌟 YOUR ROLE & RESPONSIBILITIES —

As a Data Science Intern, you will work on cutting-edge AI research projects at the intersection of healthcare and machine learning. Your project will be defined collaboratively based on your skills and interests, as well as our team’s current priorities in advancing healthcare AI.

What you’ll work on:

• Design and implement state-of-the-art deep learning architectures for complex healthcare applications

• Explore multimodal AI approaches combining vision and language models

• Advance GenAI systems leveraging the latest large language models

• Investigate cutting-edge retrieval techniques

• Develop robust evaluation frameworks and uncertainty quantification methods

• Work with agentic AI systems and advanced reasoning pipelines

• Design novel evaluation protocols that balance performance, safety, and clinical relevance

• Benchmark and compare performance across different model architectures (both closed-source and open-source)

👤 WHO YOU ARE

Required:

• Master’s degree (M2) or final year of engineering school in Machine Learning, Computer Science, Mathematics, Physics, or related field

• Strong foundation in machine learning, deep learning, and statistics

• Proficiency in Python and experience with ML frameworks (PyTorch or TensorFlow)

• Experience with scikit-learn, DGL, Transformers, or similar libraries

• Familiarity with version control systems (Git)

• Ability to read and implement research papers

• Strong analytical and problem-solving skills

• Professional working proficiency in French and English.

• Team spirit and eagerness to learn

Nice-to-have:

• Experience with NLP, LLMs, or graph neural networks

• Familiarity with healthcare/MedTech domains

1. Screening Call – An initial conversation with the hiring manager to understand your background and see if there’s a good fit.

2. Technical Interview – A discussion with our team to review a take-home test you will do, and dive deeper into your expertise.

3. Cultural Fit Interviews – One interview to ensure alignment with our values and team dynamics.