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Principal Machine Learning Engineer - Applied AI & LLMs
Location
Paris, Paris, France
Work type
Hybrid
Employment
Full Time
Experience
10-15 years
Compensation
Compensation not disclosed
Posted
8h ago
Summary and responsibilities
Role overview
Summary
This Principal Machine Learning Engineer role at Doctolib involves leading cross-cutting technical challenges across all AI teams, defining ML architecture, standardizing evaluation frameworks, and spreading strong engineering practices. The position requires deep expertise in ML/AI, particularly with LLMs, and a focus on building innovative, impactful products for healthcare professionals and patients.
About the Role
Doctolib is seeking a Principal Machine Learning Engineer to join its Data Science and AI organization in Paris, France. This cross-functional role will drive technical strategy, architecture, and engineering standards across Clinical AI, Productivity, Phone Assistant, and Automatic Speech Recognition (ASR) teams. You will solve complex machine learning challenges, develop scalable AI infrastructure, and guide teams in building reliable, safe, and effective AI solutions that improve healthcare experiences for 400,000 healthcare professionals and 80 million patients.
Responsibilities
Technical Strategy and Architecture
Lead cross-team ML architecture decisions, covering model selection, production deployment, and build-versus-buy strategies. Develop standardized evaluation frameworks for machine learning models and AI agents, and establish production infrastructure standards for model and prompt versioning, guardrails, uncertainty quantification, cost optimization, and observability.
Lead the technical design of agentic AI solutions and define reusable AI capabilities for product teams. Conduct architecture reviews, guide Staff and Senior ML Engineers, and promote engineering best practices across the Data Science and AI organization. Collaborate with Product, Legal, and Compliance teams to ensure safe AI deployment and compliance with GDPR, MDR, and the EU AI Act.
Requirements
You should have at least 10 years of experience in machine learning and AI, including three or more years in Staff-level, Principal-level, or equivalent technical leadership roles. You must demonstrate experience leading complex technical initiatives across multiple teams and possess deep expertise in at least two areas: clinical NLP, LLM fine-tuning and evaluation, automatic speech recognition, retrieval-augmented generation (RAG), or reinforcement learning.
Advanced Python skills and expertise in PyTorch, Transformers, and vLLM are essential, alongside proven experience deploying production ML systems on AWS or GCP. A PhD in Computer Science, AI, Statistics, or a related field is preferred, or equivalent research experience. Excellent communication skills and the ability to align stakeholders and explain complex technical decisions are also required.
Nice to Have
Publications at leading AI and ML conferences, such as NeurIPS, ICLR, or ACL, or in medical informatics are advantageous. Experience with European healthcare regulations, including GDPR, MDR, and the EU AI Act, as well as previous work with clinical data or healthcare applications, is also desirable.
About Doctolib Tech
Doctolib develops a cloud-native healthcare platform supporting web and mobile applications across multiple languages and medical specialties. Its technology stack includes Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native. The company is committed to using AI responsibly to empower healthcare professionals and patients.
What We Offer
Doctolib provides comprehensive health insurance for employees and their children, 25 days of paid annual leave plus up to 14 RTT days, and free mental health and coaching services through Moka.care. Employees can work abroad for up to 10 days annually and receive lunch vouchers worth €8.50, with €4.50 covered by Doctolib.
Additional benefits include subsidies for sports memberships and creative classes, 50% reimbursement of public transport subscriptions, and an additional month of parental leave through the Parent Care Program. Support for caregivers and employees with disabilities includes adapted remote-working arrangements, additional medical leave, and psychological support. Relocation assistance, premium AI development tools, and dedicated training are also available.
Interview Process
The recruitment process includes HR screening, a hiring manager interview, a technical interview, a technical case study, a behavioral interview, and at least one reference check.
Job Details
Position: Principal Machine Learning Engineer
Employment Type: Permanent, full-time
Location: Paris, France
Work Mode: Hybrid, with up to two remote days per week
Start Date: As soon as possible
Equal Opportunity and Data Privacy
Doctolib welcomes applicants from all backgrounds and evaluates candidates based on their qualifications and motivation. Reasonable adjustments are available to support candidates with disabilities during recruitment.
Candidate information is processed for recruitment purposes in accordance with Doctolib's data privacy policies.
Updated 8h ago
Candidate fit
Skills and qualifications
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Experience
10-15 years
How this role is positioned
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Employment
Full Time
Contract duration
Permanent
Hiring type
Direct
Global hiring
Location specific
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Compensation
Compensation not disclosed
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Company
Doctolib
Team size
Growing team
Location
Paris, Paris, France
At Doctolib, we’re reinventing the daily lives of health professionals and empowering people to live healthier across Europe. More than 3,000 Doctolibers across France, Germany, Italy, the UK and the Netherlands are building a new generation of AI-powered technologies and services, trusted by 520 000 health professionals and over 90 million patients every day. AI is at the heart of how we build and how we work. At Doctolib, AI fluency is a core skill for every team member: we foster a culture leveraging AI to drive efficiency, quality, and impact at scale.
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Principal Machine Learning Engineer - Applied AI & LLMs
Paris, Paris, France • Full Time