--- title: 'Senior IA Inference Engineer (x/f/m) at Doctolib' canonical: 'https://feeny.ai/job/senior-ia-inference-engineer-x-f-m-doctolib-paris-s43rw7pxvkwq' type: 'job' last_seen: '2026-10-20' --- # Senior IA Inference Engineer (x/f/m) at Doctolib - **Company:** Doctolib - **Location:** Paris, France - **Posted:** 2026-10-16 - **Last confirmed live:** 2026-10-20 - **Apply:** https://job-boards.greenhouse.io/doctolib/jobs/8018820003 ## Job description Set a new pulse for healthcare! We are looking for a Senior Inference Engineer to join the ML Platform (TIGER) team in AI & Machine Learning. Your mission will be to power Doctolib's AI-driven healthcare products — from Consultation Assistant to Phone Assistant and Health Companion — by owning the self-hosted LLM serving platform that keeps the most sensitive patient data within infrastructure Doctolib controls. You will build and operate the shared foundations that every AI feature team relies on: deploying, tuning, and scaling open-weight models across our GPU fleet, contributing directly to faster, safer, and more cost-efficient AI for care teams and patients across Europe. Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients. ## What you'll do Your responsibilities include but are not limited to: - Build the shared LLM serving foundations with MLOps engineers — define the serving stack, GPU capacity planning, and deployment automation for open-weight models (Gemma, Mistral, Llama, Qwen, and their fine-tuned variants) on Ray Serve / Anyscale, while shaping the evolution toward Kubernetes-based orchestration - Own the model registry and promotion path — establish clear processes for versioning, validating, and promoting models into production, benchmark performance and output quality under realistic workloads, and maintain the curated model catalog together with the Agents Platform team - Optimize inference performance and efficiency — operate and tune serving engines (vLLM, Triton Inference Server, TensorRT-LLM) to reduce time-to-first-token, inter-token latency, and cost per token through batching, caching, quantization, and parallelism strategies across our GPU fleet (L4 to H200) - Own production reliability and disaster recovery — define SLOs, run load tests before launches, implement safe rollouts, rollbacks, and autoscaling, and participate in on-call and incident response - Make serving performance and costs measurable — build Datadog dashboards, alerting, and cost reporting to track latency, GPU utilization, and inference spend, and identify opportunities to improve resource efficiency - Keep the inference stack secure, compliant, and evolving — work with Security and Privacy on network isolation, data residency, and auditability, while continuously assessing new models, serving engines (such as SGLang), and GPU generations ## 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'll be a great fit if you: - Have 5+ years of software or computer engineering experience, including hands-on production experience with at least one LLM serving engine (vLLM, SGLang, TensorRT-LLM, TGI, or Triton) — ideally having chosen, introduced, tuned, or scaled one in production, not just run it with defaults - Are proficient in Python and Terraform, with a solid understanding of transformer inference mechanics: prefill vs. decode, KV cache, batching strategies, and why a model is compute- or memory-bound on a given GPU - Have strong experience running GPU workloads on Kubernetes or a managed Ray / Anyscale platform, and a performance engineering mindset — you design reproducible benchmarks, read profiler output, and back decisions with numbers - Are comfortable owning production reliability: observability, incident response, and on-call are a natural part of the role - Have excellent communication and collaboration skills, high agency, a pragmatic build-vs-buy approach, and are comfortable working in a scope that is still taking shape - Are fluent in English It would be fantastic if you: - Have experience with distributed serving frameworks (KServe, llm-d, NVIDIA Dynamo), including disaggregated prefill/decode or KV-cache-aware routing, or with serving Mixture-of-Experts, multimodal models, or many LoRA adapters on shared base models - Have GPU kernel experience or deep profiling skills (CUDA, Triton, Nsight), or have contributed to open-source inference projects - Have experience in regulated environments (healthcare, finance, public sector) and with frameworks such as GDPR, HDS, ISO 27001, or SOC 2 ## Our stack - Programming languages: Python, plus comfort reading/debugging a systems language (C++, Rust, or Go) - Cloud providers: GCP / AWS / Azure - Serving orchestration: Ray Serve / Anyscale (GCP), with Kubernetes (GKE) + GPU scheduling as an emerging parallel target - LLM serving engines (in production): vLLM, Triton Inference Server, TensorRT-LLM (also evaluating SGLang and other emerging engines) - Models: Self-hosted open-weight LLMs (Gemma, Mistral, Llama, Qwen), fine-tuned in-house - Experiment tracking & model registry: MLflow - GenAI gateway: LiteLLM - LLM evaluation & observability: Braintrust - GPUs: NVIDIA L4, A10G, L40S, RTX 6000 Pro, A100 (40GB/80GB), H200 - Container / Infra as code: Docker, Terraform, Helm, Kustomize - Observability: Datadog - Data warehouse / storage: GCP BigQuery / GCS / AWS S3 - And any other tool you deem relevant! 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](https://careers.doctolib.com/ai-careers/). Want to learn more about our tech culture and environment? Visit the [Doctolib Tech site](https://careers.doctolib.com/tech-doctolib/). ## 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 - ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave and 75% during the second, covered by Doctolib - 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 Our interview process - HR interview by phone (45 minutes) - Hiring manager interview (1 hour) - Technical case study (1 hour) - Behavioral interview (1 hour 30 minutes) - At least one reference check We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our [candidate experience page](https://careers.doctolib.com/tech-doctolib/getting-hired/). Job details - Permanent position - Tech stack: Python, vLLM, TensorRT-LLM, Triton, Ray Serve - Full-time - Paris, France - Hybrid work setup (up to 2 remote days per week) - Start date: as soon as possible We welcome everyone 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, or 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! ## Your data privacy All information provided is processed by Doctolib for application management. For data processing details, click here: [France](https://doctolib.legal/B2C-Privacy-Policy-Career-FR). Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights. ## About Doctolib ## Core Business - **Primary industry**: Healthcare information technology (healthtech) / Software Development - **Target customers**: B2B (healthcare professionals across 120+ specialties) and B2C (patients managing their health journey) - **Mission or purpose statement**: “Build together the healthcare we all dream of” – making healthcare more human, sustainable, and accessible. The company is a certified B Corp and mission-driven. ## Products & Services - **Appointment Booking** – 24/7 online scheduling, waitlist management, calendar optimization, reminders and delay notifications. - **Practice Efficiency (Digital Secretariat)** – Tools for patient base management, task manager, openings/absences, recall campaigns, and analytics. - **Clinical & Care Cooperation** – Electronic health records (EHR), document management, secure messaging, prescribing, billing engine, and AI assistants for documentation and decision support. - **Health Companion (Patient App)** – A mobile app offering prevention campaigns, early detection programs, personalized guidance via an AI assistant, video consultations, and messaging with professionals. - **AI Consultation Assistant** – Structured transcription of consultations; has supported 5 million consultations. - **AI Phone Assistant** – Virtual assistant handling bookings and messages 24/7. - **Financial Solutions** – Simplifies billing and insurance processes for healthcare professionals. - **Platform & APIs** – Internal platform for modular development; data import/export, CRM integrations, and partner programs. ## Market Standing - **Valuation/Market Cap**: Not disclosed (private company) - **Key Metric**: Annual Revenue EUR 257.6M (latest available); Total Funding USD 816M across 10 rounds - **Notable Investors/Partners**: General Atlantic (lead in Series E), Eurazeo (Series D lead), Accel (Series B lead), and others. Acquired Dott.it, Tanker, and Appocrate. - **Growth Signals**: - 90 million patients and 420,000 healthcare professionals use the platform. - 2,900+ employees (up from ~2,618 as per LinkedIn; monthly headcount growth +1.0%). - Operating in France, Germany, Italy, Netherlands, with presence in Switzerland and UK. - Tech team of 900+ experts; AI features deployed in production (e.g., AI Consultation Assistant used in 5M consultations). ## Competitive Advantages - **Network effects**: Large, two-sided marketplace connecting millions of patients with hundreds of thousands of professionals across Europe. - **Deep healthcare expertise**: Over a decade of experience, solutions adapted to 120+ specialties and local regulations. - **AI-first innovation**: Proprietary datasets, research lab, and production AI assistants that improve clinical efficiency. - **Trust and compliance**: Certified B Corp, ISO 27001, HDS (health data hosting) – high security and privacy standards. - **Platform modularity**: Cloud-native, distributed architecture that allows rapid adaptation to new countries and specialties. ## Strategic Focus - **AI integration**: Scaling AI Consultation Assistant, AI Phone Assistant, and AI-powered clinical decision support. - **Preventive and continuous care**: Shifting from reactive treatment to proactive health management via the Health Companion app. - **Geographic expansion**: Deepening presence in existing European markets and entering new regions. - **Platform modularization**: Building reusable components to accelerate product development and partner integrations. - **Mission-driven growth**: Maintaining B Corp status while expanding revenue and impact. ## Why Work Here - **Culture**: Mission-driven, B Corp certified, collaborative environment focused on social impact. Employees report a strong sense of purpose. - **Work policy**: Flexible – hybrid and office-based modes available. Option to work from EU countries and the UK for up to 10 days per year. - **Benefits**: - Health insurance 100% paid for employee and children. - 25 paid vacation days + up to 14 RTT days annually. - Free mental health and coaching services (Moka.care). - On-site gym with group classes (Paris office). - One additional month of parental leave on top of legal leave (Parent Care Program). - Lunch vouchers (Swile card), sports/club subsidy. - Solidarity Days (2 days/year for health charities). - **Engineering culture**: 900+ tech team, dedicated onboarding (Doctolib Academy), continuous training, access to best AI tools, and internal mobility opportunities. - **Employer rating**: 3.6/5 on LinkedIn (923 reviews) – work-life balance 3.7, culture 3.7, compensation 3.3. ## Sources 1. [careers.doctolib.com](https://careers.doctolib.com/) 2. [careers.doctolib.com/tech-doctolib](https://careers.doctolib.com/tech-doctolib/) 3. [linkedin.com/company/doctolib](https://www.linkedin.com/company/doctolib) 4. [jobsbyculture.com/companies/doctolib](https://jobsbyculture.com/companies/doctolib) 5. 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