Machine Learning Research Internship (x/f/m)

Join Europe's leading healthcare technology company for a 6-month Machine Learning research internship in our Paris office. At Doctolib, you'll tackle real-world healthcare challenges using cutting-edge machine learning, working directly with our AI teams to impact millions of lives.

As a Machine Learning Research intern, you’ll be paired with ML engineers and researchers who act as mentors, collaborating with you on real-world projects.

We work with simple regressions as well as sophisticated LLM pipelines, we’ve shipped AI-native products and are pioneering the next wave of AI innovation in the health space. Your research will directly influence products used by 400,000+ healthcare practitioners serving 90 million patients across Europe.

About The Role

Machine learning is a key part of Doctolib's mission to improve healthcare. Healthcare is a complex and dynamic environment which creates unique opportunities for ML experimentation, allowing us to incorporate new ideas to improve patient care and medical practice efficiency.

Researchers at Doctolib are responsible for building models, strategies, and systems that optimize healthcare scheduling, the clinical documentation process, help practitioners gain time and improve the care they’re able to provide. The end goal is for improved health outcomes: healthier people, for longer, with greater autonomy.

We're looking for candidates with machine learning experience in either an applied or academic context. A good candidate should have a deep understanding of a wide variety of ML techniques, and be motivated to experiment with things like model architectures and data processing to generate novel healthcare insights or improve current systems.

At the end of your internship :

• You'll have gained an understanding of the differences between textbook machine learning and its application to complex, real-world healthcare data.
• You'll have learned to bridge the gap dealing with challenges like trustworthiness, accuracy and safety, transparency and explainability, data privacy, and multiple modalities.
  
  
  

Depending on the specific scope of your internship, it is possible that the research findings will be suitable for academic publication.

About You

You could be our next team mate if you are:

• A Master’s student with practical experience working on ML problems
• A strong programmer (we use Python)
• Enthusiastic about collaborative work
• Eager to ask questions, admit mistakes, and learn new things
• Interested in improving healthcare through technology
• Fluent in two of the following languages: English, French or German
  
  
  

Are you convinced that you have exactly what it takes for the position? Then we encourage you to apply. Even if you don't meet every requirement, you might be exactly the right future Doctoliber for this or other positions!

What we offer

• A flexible workplace policy offering both hybrid and office-based mode
• Lunch voucher with Swile card
• Work Council subsidy to refund part of sport club membership or creative class
• Reimbursement of public transportation
  
  
  

The interview process

• An interview with our Talent Partner (30 minutes)
• A case study interview with the Hiring Manager (1 hour)
  
  
  

Details of the job

• Internship
• Duration : 6 months
• Start date : Q1/Q2 2025
• Location : Levallois-Perret
• Salary : To be defined
• Working mode : Hybrid - 3 days a week at the office
  
  
  

At Doctolib, we believe in improving access to healthcare for everyone - regardless of where you come from, what you look like. This translates into our recruitment process: Doctolib is an equal opportunity employer. We don't just accept diversity at Doctolib, we respect and celebrate it!

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib or refer someone you know, regardless of your and their gender, religion, age, sexual orientation, ethnicity, disability, or place of origin. If you have a disability, let us know if there's any way we can make the interview process smoother for you!