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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 simplify the access and quality of care for all. In this role, you'll have the opportunity to work with a team of talented ML Engineers, Software Engineers, MLOps and Healthcare professionals to develop and deploy AI models that will have a real impact on people's lives. You will work at simplifying how patients find their healthcare practitioner, handle their care plan in the long term and work with business team to contribute expansion of Doctolib in several new markets. Doctolib is looking for a Machine Learning Engineer to join our ML Engineering team in charge of our patient solutions.
Job Responsibility:
Find the right technical solution to solve the product domain goals
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
Requirements:
Have strong analytical skills, are result oriented and user first
Have between 3/7 years of experience in the domain of Machine Learning / Deep Learning / AI Engineering, including taking models from prototype to production at scale
Have experience in Information Retrieval and modern retrieval stacks, including some of the following: Hybrid search (sparse + dense), Large-scale embeddings and vector databases, Multi-stage retrieval and re-ranking pipelines, RAG architectures and retrieval pipelines on multimodal use cases, Tools and MCP-based integrations to bring in external data and capabilities
Proficient in LLM/VLM application development, including: Fine-tuning LLM and VLM models, Mixture-of-Experts (MoE) architectures (via LiteLLM or Model Garden), Knowledge Distillation, Prompt engineering and tool use, Evaluation and benchmarking of LLM/VLM systems
Have hands-on experience with agentic AI (e.g. building and orchestrating agents on top of ADK)
Have demonstrated strong scientific rigor and benchmarking skills: Designing metrics aligned with product goals, Running controlled end to end experiments with W&B, MLFlow or Braintrust, Analyzing and communicating results to guide product and technical decisions
Have experience with large scale applications in production (monitoring, reliability, performance, observability)
Nice to have:
Have experience in B2C marketplace
Have experience in other ML methodologies : pattern mining, recommendation, experimentation or causal inference
What we offer:
Free health insurance for you and your children
Parent Care Program: receive one additional month of leave on top of the legal parental leave
Free mental health and coaching services through our partner Moka.care
For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy
Work Council subsidy to refund part of sport club membership or creative class