Senior AI Engineer – Search & Recommendation – Patient Team (x/f/m)

Doctolib; France; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Free comprehensive health insurance

25 days paid vacation

Mental health and coaching services

Flexibility days: work from abroad

Lunch vouchers

Transport subsidy

DoctoGrowth program

ParentCare program

Job summary

Doctolib is hiring a Senior AI Engineer for the Patient team in Paris. You will design and own the production search and recommendation architecture to help patients navigate to the right care, using vector search, RAG, and LLM-based rerankers.

Collaborate with ML engineers and product teams to ship impactful AI features with strong observability. You will ship end-to-end retrieval systems on a cloud-native platform, ensuring low latency and robust data quality.

Qualifications

• Proven experience shipping AI/ML models to production
• Strong background in building search or recommendation systems
• Experience with production-grade data pipelines and monitoring

Responsibilities

• Design and build production search and recommendation architecture with vector search and LLM-based components
• Establish baselines with prompts, RAG, and model selection
• Implement evaluation, observability, and feedback loops for offline/online validation
• Collaborate with ML engineers, PMs and SWE to ship AI-powered features

Skills

Production deployment

AI engineering

Search systems

MLOps

Performance monitoring

Tools

Vector search

RAG

LLMs

Embeddings

Job description

Join our mission, join Doctolib!We are looking for a Senior AI Engineer to join the Patient team in Paris.The Patient domain sits at the heart of Doctolib's mission: ensuring everyone has better access to the care they need, receives better care from health professionals, and can actively prevent health problems to improve their wellbeing.You’ll design the search and recommendation engines behind our health companion, helping 100M patients across Europe instantly navigate to the exact care they need while delivering trusted, curated insights at every step. The retrieval and recommendation architecture you own will directly shape how relevant, fast, and trustworthy that experience is for every one of them.

Responsibilities

• Design and build the production search & recommendation architecture: full retrieval, ranking, reranking pipeline with standard and off-the-shelf components (vector search, semantic retrieval, LLM/managed rerankers).
• Establish strong baselines first (prompts, RAG, model selection) before reaching for custom ML.
• Build evaluation and observability into every stage, with offline and online evaluation.
• Set up the data/event feedback loops that drive iteration and feed deeper ML later.
• Improve search relevance and ranking on Patient facing products , raising result qualityOwn production quality: latency reliability, monitoring, and maintainability.
• Partner with ML Engineers and collaborate closely with PMs and SWEs to define, build, and ship AI-powered features that deliver measurable value to users and the business.

Before you read on:

Who you are

• Production deployment: ability to ship algorithms to production (ECS-based service on AWS)
• Strong analytical mindset: result-oriented, patient-first approach
• Significant experience as a Software or/and AI engineer shipping search or recommendation systems to production.
• Hands-on experience building end-to-end retrieval: ranking, reranking pipelines and familiar with nDCG, MAP, Recall@k, MRRAI-engineering proficiency: turning foundation models and off-the-shelf components into production systems: embeddings & vector search, semantic retrieval, RAG, LLM-based or managed rerankers (e.g. Vertex AI). You can succeed without training a model from scratch
• Architecture-first approach: you build the system, baselines, evals, and feedback loops with standard tooling before reaching for custom ML, and know when to partner with ML Engineers to break a ceiling
• Evaluation & observability built into every stage (retrieval, ranker, reranker) — offline and online eval, A/B testing, position-bias handling, monitoring
• Production deployment — ability to ship reliable, low-latency services to production (hundreds-of-ms SLAs), with care for data quality and long-term maintainability

Now, it would be fantastic if you:

• Experience at a B2C marketplace (e-commerce, hospitality, travel)
• Additional ML methodologies: pattern mining, recommendation systems, experimentation, or causal inference
• Have experience with search engines or information retrieval concepts
• Have exposure to learning-to-rank or feature engineering (for breaking ceilings later, alongside ML Engineers)
• Have experience in a healthcare or other regulated domain (GDPR / HDS)

Life at Doctolib Tech

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.

We also invest in open, applied AI research. For example, ourDoctoBERT project introduces open-source medical language models trained for French clinical text, with applications in named entity recognition, classification, and retrieval. Read the DoctoBERT practical guide to learn more about how we bring deep AI research into practical healthcare applications.

Want to learn more about our tech culture and environment? Visit the Doctolib Tech site.

What we offer

• 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
• Enrollment in Doctolib's long-term employee value sharing plan called DoctoGrowth
• ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave, and 75% during the second, covered by Doctolib
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support

The interview process

• A first interview with a member of the Talent Acquisition team
• A coding interview
• An agentics system design
• A behavioural interview
• Reference check

Job details

• Permanent position
• Full Time
• Workplace: Levallois
• Start date : As soon as possible

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

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.

To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of! All information provided is processed by Doctolib for application management. For data processing details, click here: Germany l France l Italy l Netherlands. Please contact hr.dataprivacy(at)doctolib.com to exercise your rights.