Senior MLOps Engineer
Alice & Bob Open · verified Oct 22, 2026 Hybrid Paris Senior ML Platform & Ops
At a glance
Senior ML Platform & Ops role at Alice & Bob. Paris.
Pay not stated ML Platform & Ops salary
RoleML Platform & Ops
SenioritySenior
LocationParis
WorkplaceHybrid
PostedAug 18, 2026 · 2mo ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run GCP systems for ML workflows, model releases and ongoing performance checks
- Help research and data teams move models out of experiments and into production
- Create dependable, scalable setups for conventional machine learning and generative AI applications
- Keep model work reproducible and observable, and advise teams on architecture, tools and GCP AI services
- Coordinate with data engineering and DevOps on data, infrastructure and CI/CD as the platform develops
What you bring
- At least seven years in ML engineering, MLOps, software engineering or a related area
- Strong Python ability and a record of operating ML systems in production
- Hands-on MLOps experience covering pipelines, deployment and monitoring
- Experience using Docker and Kubernetes or GKE, plus familiarity with a modern ML framework
- LLM or generative AI experience and fluency in English
Who this fits
This senior role suits someone who can work across research and engineering teams and help colleagues adopt AI practices. The position is based in Paris with a hybrid arrangement; remote work can be used up to forty percent per month. You should be comfortable with an onsite technical interview.
From the employer
Alice & Bob is developing the first universal, fault-tolerant quantum computer to solve the world’s hardest problems.
The quantum computer we envision building is based on a new kind of superconducting qubit: the Schrödinger cat qubit 🐈⬛. In comparison to other superconducting platforms, cat qubits have the astonishing ability to implement quantum error correction autonomously!
We're a diverse team of 250+ brilliant minds from over 35 countries united by a single goal: to revolutionise computing with a practical fault-tolerant quantum machine. Are you ready to take on unprecedented challenges and contribute to revolutionising technology? Join us, and let's shape the future of quantum computing together!
About the role
We are building a modern, AI-ready Data Platform on Google Cloud Platform.
As a Senior MLOps / LLMOps Engineer, you will help turn ML and AI experiments into reliable, production-ready solutions. You will work closely with researchers, data scientists and engineers to build the infrastructure and practices needed to train, deploy and operate models at scale.
You will also play an important role in helping teams adopt AI technologies and best practices across the company.
Responsibilities
- Build and maintain MLOps / LLMOps infrastructure on GCP, including ML pipelines, model deployment and monitoring.
- Help researchers and data scientists bring models from experimentation to production.
- Design reliable and scalable solutions for both traditional ML and GenAI / LLM use cases.
- Ensure models and experiments are reproducible, observable and maintainable.
- Advise teams on ML/AI architecture, tooling and best practices.
- Share knowledge and help teams make effective use of GCP AI services.
- Work closely with Data Engineering and DevOps teams on data, infrastructure and CI/CD.
- Contribute to the evolution of the ML/AI platform as the company's AI needs grow.
Requirements
- 7+ years of experience in ML Engineering, MLOps, Software Engineering or a related field.
- Strong Python skills and experience running ML systems in production.
- Solid experience with MLOps, including pipelines, deployment and monitoring.
- Experience with GCP / Vertex AI is a strong plus.
- Experience with Docker and Kubernetes/GKE.
- Familiarity with modern ML frameworks such as PyTorch, TensorFlow or scikit-learn.
- Experience with LLMs / GenAI.
- Strong analytical and communication skills, with the ability to work with both technical and research teams.
- Fluent in English.
Recruitment Process
- Screening call with Doriane (30 min)
- Hiring Manager interview (45 min)
- Technical onsite Interview - (90min)
- Leadership Interview (30 min)
- Fit Interview (30 min)