Senior ML Ops (x/f/m)
- Salary
- Not stated
- Level
- Senior
- Work type
- Not stated
- Visa
- Not stated
Open. First seen 2 October 2026.
The team: Engineering HIRES STEADILY
This role is one of 71 open in Engineering. 20 were posted in the last 30 days and the oldest in January: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (71 of 71), Java (68 of 71), Kotlin (66 of 71), React (66 of 71), React Native (66 of 71), Ruby on Rails (66 of 71), TypeScript (66 of 71)
OTHER ROLES ON THIS TEAM
- Senior Agents Platform Engineer (x/f/m) posted Oct 16
- Senior Agents Platform Engineer (x/f/m) posted Oct 16
- Senior IA Inference Engineer (x/f/m) posted Oct 16
- Senior IA Inference Engineer (x/f/m) posted Oct 16
- Software Engineer Intern - Fullstack (x/f/m) - Berlin - March 2027 posted Oct 12
- Software Engineer Intern - Fullstack (x/f/m) - Berlin - March 2027 posted Oct 12
- Software Engineer Intern - Fullstack (x/f/m) - Amsterdam posted Oct 12
- Software Engineer Intern - Fullstack (x/f/m) - Amsterdam posted Oct 12
- Software Engineer Intern - Fullstack (x/f/m) - Milano posted Oct 12
- Software Engineer Intern - Fullstack (x/f/m) - Milano posted Oct 12
- Software Engineering Intern - Fullstack (x/f/m) - Niort posted Oct 12
- Software Engineering Intern - Fullstack (x/f/m) - Niort posted Oct 12
- Software Engineering intern - Fullstack (x/f/m) - Nantes posted Oct 12
- Software Engineering intern - Fullstack (x/f/m) - Nantes posted Oct 12
- Software Engineering Intern - Fullstack (x/f/m) - Paris posted Oct 12
- Software Engineering Intern - Fullstack (x/f/m) - Paris posted Oct 12
- Director of AI Developer Experience - Platform Engineering (x/f/m) posted Oct 6
- Director of AI Developer Experience - Platform Engineering (x/f/m) posted Oct 6
- Senior ML Ops (x/f/m) posted Oct 2
- Senior Software Engineer - Node.js/TypeScript (x/f/m) posted Sep 11
- Senior Software Engineer - Node.js/TypeScript (x/f/m) posted Sep 11
- Senior Data Ops engineer (x/f/m) posted Aug 25
- Senior Data Ops engineer (x/f/m) posted Aug 25
- Staff Site Reliability Engineer (x/f/m) posted Aug 11
- Staff Site Reliability Engineer (x/f/m) posted Aug 11
- Staff Site Reliability Engineer (x/f/m) posted Aug 11
- Staff Site Reliability Engineer (x/f/m) posted Aug 11
- Engineering Manager - Site Reliability & Observability (x/f/m) posted Aug 6
- Engineering Manager - Site Reliability & Observability (x/f/m) posted Aug 6
- Engineering Manager - Site Reliability & Observability (x/f/m) posted Aug 6
- Engineering Manager - Site Reliability & Observability (x/f/m) posted Aug 6
- Senior Site Reliability Engineer (x/f/m) posted Jul 28
- Senior Site Reliability Engineer (x/f/m) posted Jul 28
- Senior Site Reliability Engineer (x/f/m) posted Jul 28
- Senior Site Reliability Engineer (x/f/m) posted Jul 28
- Senior Software Engineer Fullstack Kotlin / React (x/f/m) posted Jul 28
- Senior Software Engineer Fullstack Kotlin / React (x/f/m) posted Jul 28
- Staff Machine Learning Engineer - Retrieval (x/f/m) posted Jul 27
- Staff Machine Learning Engineer - Retrieval (x/f/m) posted Jul 27
- Senior Site Reliability Engineer - Database (x/f/m) posted Jul 13
- Senior Site Reliability Engineer - Database (x/f/m) posted Jul 13
- Senior Software Engineer FullStack Kotlin / React - Berlin (f/m/d) posted Jul 6
- Senior Software Engineer FullStack Kotlin / React - Berlin (f/m/d) posted Jul 6
- Senior Machine Learning Engineer - Orchestration - Applied AI & LLMs (x/f/m) posted Jul 3
- Senior Machine Learning Engineer - Orchestration - Applied AI & LLMs (x/f/m) posted Jul 3
- Senior Machine Learning Engineer - Applied AI & LLMs (x/f/m) posted Jun 1
- Senior Machine Learning Engineer - Applied AI & LLMs (x/f/m) posted Jun 1
- Principal Machine Learning Engineer - Applied AI & LLMs (x/f/m) posted May 29
- Principal Machine Learning Engineer - Applied AI & LLMs (x/f/m) posted May 29
- Senior Site Reliability Engineer - Observability (x/f/m) posted May 11
- Senior Site Reliability Engineer - Observability (x/f/m) posted May 11
- Senior MLOps Engineer - Data Ingestion - Paris posted Apr 7
- Senior MLOps Engineer - Data Ingestion - Paris posted Apr 7
- Staff DataOps Engineer (x/f/m) posted Mar 23
- Staff DataOps Engineer (x/f/m) posted Mar 23
- Senior AI Engineer (x/f/m) posted Mar 2
- Senior AI Engineer (x/f/m) posted Mar 2
- Senior AI Engineer (x/f/m) - Phone Assistant posted Feb 13
- Senior AI Engineer (x/f/m) - Phone Assistant posted Feb 13
- Engineering Manager - Observability & Reliability Engineering Obsession (x/f/m) posted Jan 26
- Engineering Manager - Observability & Reliability Engineering Obsession (x/f/m) posted Jan 26
- Engineering Manager - Observability & Reliability Engineering Obsession (x/f/m) posted Nov 7
- Engineering Manager - Observability & Reliability Engineering Obsession (x/f/m) posted Nov 7
- Staff Mobile Engineer - React Native (x/f/m) posted Nov 4
- Staff Mobile Engineer - React Native (x/f/m) posted Nov 4
- Senior Staff Machine Learning Engineer - Clinical - AI Teams (x/f/m) posted Oct 29
- Senior Staff Machine Learning Engineer - Clinical - AI Teams (x/f/m) posted Oct 29
- Senior Site Reliability Engineer - Observability (x/f/m) posted Oct 2
- Senior Site Reliability Engineer - Observability (x/f/m) posted Oct 2
- AI Talent Pool posted Jan 17
From the team and dates on Doctolib's own job board.
About the role
Set a new pulse for healthcare!
We are looking for a Senior MLOps Engineer to join the ML Platform (TIGER) team in Artificial Intelligence & Machine Learning.
Your mission will be to power every ML and AI initiative at Doctolib — from experiment to reliable production service. You will build and operate the foundations that let data scientists, ML engineers, and AI teams ship models and agents safely, fast, and at scale, from classic machine learning to self-hosted generative AI. You will contribute directly to the reliability and performance of AI-powered features that improve the daily lives of millions of patients and thousands of healthcare professionals 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:
- Partner with data scientists, ML & AI engineers to take models from experimentation to reliable, scalable production deployment.
- Operate and evolve the orchestration layer for training, serving and evaluation workloads, built on GCP and AWS using Kubernetes (GKE) and Ray-based platforms (Anyscale) — including CI/CD, versioning and automated testing pipelines that carry a model from the registry to a served endpoint.
- Build the tools, templates and best practices (Terraform modules, Kubernetes CRDs and operators, GitOps workflows, internal libraries) that let any ML team deploy and operate their models and agents safely and consistently.
- Ensure the availability, reliability and performance of ML systems in production across training, serving and the agents platform; define and track SLOs; take part in on-call and incident response for the whole stack.
- Build and maintain observability for ML systems: infrastructure and model health via Datadog, and evaluation/quality signals via Braintrust, catching regressions before they reach users.
- Work hand in hand with AI inference engineers on the shared foundations of our self-hosted LLM stack (model registry, deployment automation, shared GPU capacity), and stay current with MLOps practices for classic ML, generative AI and agentic systems alike.
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 prior experience as an MLOps Engineer, Cloud Engineer for ML applications, AI Infrastructure Engineer, or Platform Engineer for AI, or in a similar role
- Are proficient in Python, Shell scripting and Terraform, with a solid understanding of machine learning algorithms, concepts and trends
- Have hands-on experience with Kubernetes in production and GitOps tools (e.g. ArgoCD), and have built MLOps pipelines for containerizing models and solutions with Docker
- Have experience with cloud platforms such as GCP (GKE, BigQuery) and/or AWS or Azure equivalents, and with observability tools such as Datadog
- Have hands-on experience with an experiment tracking/model registry tool (e.g. MLflow) and an LLM evaluation/observability tool (e.g. Braintrust)
- Are a strong team player with excellent communication and documentation skills, comfortable with an evolving scope, and pragmatic about build vs. buy decisions
It would be fantastic if you:
- Have hands-on experience with Kubernetes-native agent abstractions (CRDs/operators, e.g. kagent) or building production agent runtimes
- Have experience with ML model quantization and optimization
- Have experience with GPU sharing/partitioning technologies (e.g. NVIDIA MIG, time-slicing, MPS)
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.
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
- 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 min)
- Hiring Manager Interview (1 hour)
- Case Study & Restitution: MLOps pipeline design and AI agent production-acceleration exercise (1h30)
- Behavioral Interview (1h30)
- 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.
Job details
- Permanent position
- Tech stack: Python / Terraform / Kubernetes
- 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. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.
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