AI Talent Pool

Doctolib is hiring an AI Talent Pool in Paris, France. Level rates it ; you can apply on Doctolib.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch, TensorFlow and scikit-learn.
Level lists 155 other open roles at Doctolib.

AI in this role

pytorchtensorflowscikit-learnmlflow

prompt-engineeringragfine-tuningml-opsnlpspeech

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.

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.

How we rate this

AI Talent Pool at Doctolib rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Talent Pool is an open job at Doctolib.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Paris, Paris, France.
The job was posted on January 17, 2024.
Applications are handled by Doctolib. Apply on Doctolib

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGFine-tuningML OpsNLPSpeechPyTorchTensorFlow

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, ML Ops, and NLP. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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