- Design and implement ML and AI solutions aligned with patient product goals, covering search, retrieval, and personalized care pathways
- Build and maintain large-scale retrieval pipelines, including hybrid search, embedding systems, vector databases, and multi-stage re-ranking architectures
- Develop, fine-tune, and evaluate LLM and VLM models using techniques such as knowledge distillation, Mixture-of-Experts (MoE) architectures, and prompt engineering
- Build and orchestrate agentic AI systems, integrating external data and capabilities through tools and MCP-based integrations
- Define metrics aligned with product goals, run controlled end-to-end experiments using W&B, MLFlow, or Braintrust, and communicate findings to guide product and technical decisions
- Deploy solutions to production in collaboration with our ML platform team, ensuring reliability, observability, and performance at scale, and act as a technical reference to elevate the team's standards and practices
- You have 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering, with a strong track record of taking models from prototype to production at scale
- You have strong experience in Information Retrieval and modern retrieval stacks: hybrid search (sparse + dense), large-scale embeddings and vector databases, multi-stage retrieval and re-ranking pipelines, RAG architectures, and tool/MCP-based integrations
- You are proficient in LLM and VLM application development: fine-tuning, MoE architectures (via LiteLLM or Model Garden), knowledge distillation, prompt engineering, and systematic benchmarking of LLM/VLM systems
- You have hands-on experience building and orchestrating agentic AI systems (e.g., using ADK)
- You demonstrate strong scientific rigor: designing metrics aligned with product goals, running controlled experiments, and communicating results clearly to both product and engineering stakeholders
- You have experience operating large-scale applications in production (monitoring, reliability, performance, observability), bring strong analytical skills, and approach your work with a user-first mindset. You are fluent in English
- Have experience in B2C marketplace environments
- Have experience in other ML methodologies: pattern mining, recommendation systems, experimentation, or causal inference
- Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.
- Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
- We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here.
- Free comprehensive health insurance (basic package) for you and your children
- 25 days of paid vacation per year, plus up to 14 days of RTT
- Free mental health and coaching services through our partner Moka.care
- Work from abroad for up to 10 days per year thanks to our flexibility days policy
- Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
- A subsidy from the work council to refund part of the membership to a sport club or a creative class
- 50% reimbursement of your public transport subscription
- Parent Care Program: receive one additional month of leave on top of the legal parental leave
- Enrollment in Doctolib's long-term employee value sharing plan called DoctoGrowth
- For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
- Relocation support in case of international mobility
- Access to the best AI tools for coding, development and dedicated training
- Recruiter Interview
- Feature Building Interview
- System Design Interview
- Behavioral Interview
- At least one reference check
- Permanent position
- Full-time
- Location: Doctolib Paris office in Levallois-Perret
- Hybrid work setup (3 days/week in the office)
- Start date: as soon as possible
Skills Required
- 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering
- Experience in Information Retrieval and modern retrieval stacks
- Experience in LLM and VLM application development
- Hands-on experience building and orchestrating agentic AI systems
- Experience operating large-scale applications in production
What We Do
Since Doctolib's creation in 2013, we have had one purpose: strive for a healthier world. 1. We aim to improve the daily lives of care teams by providing them with a new generation of technologies and services. 2. We aim to improve health for all, by offering a fast and frictionless journey for all care episodes, creating new ways for people to receive care and empowering them to become actors of their health. At Doctolib, we are honored to work in the healthcare field and we believe that innovation in healthcare should be handled differently. We apply 4 guiding principles in everything we do: 1. We create helpful solutions for care teams and people. 2. We serve everyone equally and create well-designed and accessible technologies. 3. We team up with our users to strive for a healthier world and act as one team. 4. We protect our users' privacy. It’s their health, their data. To achieve our purpose, we are assembling a team dedicated to improving healthcare, with a human-centric approach and an entrepreneurial mindset. www.doctolib.com









