Senior AI Engineer - Search & Recommendation

Doctolib; Paris; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Free health insurance

Lunch vouchers

RTT days

Work from abroad

Mental health support

Transport subsidy

Job summary

Doctolib is seeking a Senior AI Engineer for the Patient team in Paris to design and deploy production-grade search and recommendation systems. You will work on vector-based retrieval, RAG, and LLM-driven features that guide millions of patients to the right care.

You will partner with ML engineers, PMs, and SWEs to ship AI-powered capabilities with strong emphasis on latency, reliability, and observability across a cloud-native platform.

Qualifications

• Significant experience shipping search or recommendation systems to production.
• Experience turning foundation models into production components (embeddings, vector search, RAG).
• Strong focus on latency, reliability, and maintainability in production.

Responsibilities

• Design and build production search & recommendation architecture with vector search and LLM components.
• Establish baselines (prompts, RAG, model selection) before custom ML.
• Implement evaluation and observability for offline and online testing.
• Create data/event feedback loops to drive ML iteration.
• Collaborate with ML engineers, PMs, and SWE to ship AI-powered features.
• Ensure low-latency, high-quality production services.

Skills

Production deployment

AI engineering

Architecture first

Retrieval & ranking

Observability

Evaluation

End-to-end retrieval

LLM-based/RAG

Tools

AWS ECS

Vector search

Semantic retrieval

Vertex AI

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.

Your 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 quality
• Own 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.

Who you are

Before you read on: if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

You could be our next team mate if you have:

1. Production deployment: ability to ship algorithms to production (ECS-based service on AWS)
2. Strong analytical mindset: result-oriented, patient-first approach
3. Significant experience as a Software or/and AI engineer shipping search or recommendation systems to production.
4. Hands-on experience building end-to-end retrieval: ranking, reranking pipelines and familiar with nDCG, MAP, Recall@k, MRR
5. AI-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
6. 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
7. Evaluation & observability built into every stage (retrieval, ranker, reranker) — offline and online eval, A/B testing, position-bias handling, monitoring
8. Production deployment — ability to ship reliable, low-latency services to production (hundreds-of-ms SLAs), with care for data quality and long-term maintainability

Nice to have

• 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, our DoctoBERT 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!

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