Senior Machine Learning Engineer - LLM- AI Teams (x/f/m)

What you’ll do

At Doctolib, we're on a mission to transform the way healthcare is delivered by leveraging the power of AI. As a Machine Learning Engineer, you'll play a critical role in developing and implementing cutting-edge AI solutions that will enable us to create an AI medical assistant that will support the Healthcare Professionals in their day to day job.

In this role, you'll have the opportunity to work with a team of talented Machine Learning Engineers, software engineers and healthcare professionals to develop and deploy AI models that will have a real impact on people's lives.

Doctolib is looking for a Senior Machine Learning Engineer to join our dedicated feature team in charge of shaping the new consultation experience powered by a medical assistant.

Let’s make a direct impact of your work with easy access to final users (practitioners) or subject matter experts to empower our Clinical Product with AI.

Your responsibilities include but are not limited to:

• Create, find or adapt model architecture, annotation or validation strategies to improve our speech recognition, summarization and medical data structuration engines
• Implement your ideas and test them
• Deploy your algorithms in production guided by our ML platform team
• Measure the uplift and continuously improve your approach 

Who you are

You could be our next team mate if you have: 

• Master's or Ph.D. degree in Computer Science, Data Science, or a related field.
• At least 5 years of experience working on Language Models, including pre-trained models like GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers).
• Proven track record of working on NLP projects, with a focus on LLM and RAG frameworks.
• Experience with deep learning frameworks such as TensorFlow or PyTorch for training and fine-tuning LLM models.

If you possess these qualifications and have a passion for pushing the boundaries of LLM, NLP and RAG frameworks, we invite you to apply for this Senior Machine Learning Engineer position.

What we offer

• Free Health Insurance for you & your family
• Quarterly or monthly bonus (based on your position)
• Up to 14 days of RTT 
• Transparent internal mobility opportunities you're welcome to apply for
• Parental care program (1 month off in addition to the legal parental leave and 0,5 days off per child when the school starts)
• Solidarity Days (2 days per year to help health charities and create a positive social impact)
• Wellbeing program (free mental health and coaching offer with our partner moka.care)
• A flexible workplace policy offering both hybrid and office-based mode
• Flexibility days allowing to work in EU countries and the UK 10 days per year 
• Lunch voucher with Swile card
• Work Council subsidy to refund part of sport club membership or creative class
• Bicycle subsidy
• Reimbursement of public transportation 
• Relocation support for international mobilities

The interview process 

• HR Screen
• Technical Deep Dive
• System Design
• Behavioral Interview
• Final interview with the DS Director
• Reference check and criminal records check
• Offer!

Job details

• Permanent position
• Full Time 
• Workplace : Doctolib Paris office in Levallois Perret
• Work mode: hybrid 3 days/week in the office
• Start date: asap
• Remuneration : fix + bonus on objectives (according to your profile)

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! 

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