AI Talent Pool
- Level
- Mid
Not stated in the posting: salary, work type, visa.
Open. First seen 2 October 2026.
About the role
Are you passionate about artificial intelligence and want to contribute to revolutionizing the healthcare sector? Doctolib develops cutting-edge AI solutions to improve access to care and facilitate the daily lives of healthcare professionals and patients. Our AI/ML teams work on large-scale projects: medical natural language processing, recommendation systems, clinical process automation, and much more.
Doctolib's standard text
We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here!
By joining our AI talent pool, you will be contacted as a priority for our future opportunities in the following areas:
The areas of expertise we are looking for :
- ML Engineering & MLops : Python proficiency, Model deployment, Evaluation frameworks (Offline/Online) & Model monitoring
- Natural Language Process (NLP) : Clinical NLP, LLM expertise Deep Learning or Speech / Language modeling
- LLMops & Generative AI : Prompt Engineering, RAG, LLM fine-tuning, Embedding models, Agent frameworks
- Automatic Speech Recognition (ASR) : Voice Activity Detection, Interactive voice assistants, audio processing, Speech-to-text
- Search, Ranking, information retrieval
- Reasoning capabilities : Logical reasoning, Multi-step reasoning, Chain-of-thought approaches
- Knowledge representation : Knowledge graphs, ontologies, Semantic modeling
- Reinforcement Learning : RL algorithms, Policy optimization, Reward modeling
Most of our positions require:
Before reading further, if you don't have the exact profile described below, but you think this job description matches your skills and aspirations, we still encourage you to apply.
- Hold a degree in computer science, applied mathematics, data science, or related field (Master's, PhD, or equivalent)
- Master machine learning and deep learning frameworks (PyTorch, TensorFlow, Scikit-learn)
- Have hands-on experience with LLMs, open and closed source Proficient in Python
- Possess strong analytical skills and a results-oriented approach
- You speak English fluently (international work environment)
It would be fantastic if:
- You have experience in healthcare or medical NLP
- You master RAG techniques, embeddings, and vector search
- You know MLOps technologies and model deployment in production (Kubernetes, Docker, MLflow)
- You have contributed to open-source projects or published in AI conferences
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, regardless of your 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!
All the information transmitted via this form is processed by Doctolib for the purpose of managing applications. For more information on how Doctolib processes your application data, click here.
If you wish to exercise your rights or if you have any questions about the processing of your data, you can write to us at hr.dataprivacy@doctolib.com.
What this role asks for
In most of Doctolib's ads
Python
Named in most of its open postings, whatever the role.
96% of this description is written for the role. The rest is Doctolib's standard text, folded away below.
Read against Doctolib's other open postings on this site.
The team: Engineering HIRES STEADILY
This role is one of 71 open in Engineering. 20 were posted in the last 30 days and the oldest in January: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (71 of 71), Java (68 of 71), Kotlin (66 of 71), React (66 of 71), React Native (66 of 71), Ruby on Rails (66 of 71), TypeScript (66 of 71)
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From the team and dates on Doctolib's own job board.
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