Senior MLOps Engineer
Paris
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou will work closely with researchers, data scientists and engineers to build the infrastructure and practices needed to train, deploy and operate models at scale.
Build and maintain MLOps / LLMOps infrastructure on GCP, including ML pipelines, model deployment and monitoring.
Design reliable and scalable solutions for both traditional ML and GenAI / LLM use cases.
From the employer’s posting
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
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.
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.
What you’ll bring
All qualificationsCore experience
- 7+ years of experience in ML Engineering, MLOps, Software Engineering or a related field.
- Leadership Interview (30 min)
- 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.
Qualification wording
7+ years of experience in ML Engineering, MLOps, Software Engineering or a related field.
Leadership Interview (30 min)
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.
Tools in this posting
- Python
- Docker
- Google Cloud (GCP)
- PyTorch
- TensorFlow
- Kubernetes
- scikit-learn
Source — Tool mentions in context
- 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.
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
- Solid experience with MLOps, including pipelines, deployment and monitoring. - Experience with GCP / Vertex AI is a strong plus. - Experience with Docker and Kubernetes/GKE.
- Experience with Docker and Kubernetes/GKE. - Familiarity with modern ML frameworks such as PyTorch, TensorFlow or scikit-learn. - Experience with LLMs / GenAI.
Benefits in the posting
Full benefits wording- A Parental plan including additional benefits such as crèche support or additional days-off to take care of under 12 years old children
- Subsidized membership with Urban Sports Club
- Mental health support with moka.care
- Half of transportation cost coverage (as per French law), or yearly allowance for the die-hard bicycle users
- Competitive health coverage, with Alan.
- French language courses covered by the company for those interested
- Research shows that women might feel hesitant to apply for this job if they don't match 100% of the job requirements listed. This list is a guide, and we'd love to receive your application even if you think you're only a partial match. We are looking to build teams that innovate, not just tick boxes on a job spec.
- Employment type
- CDI
From the employer’s posting.
Job description
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)
Employment type
CDI
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Paris
- Direct IP Compensation: Earn substantial bonuses for driving the core patents that define our quantum architecture. - Flexible remote policy, up to 40 % a month - A Parental plan including additional benefits such as crèche support or additional days-off to take care of under 12 years old children
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 19, 2026
- Recorded sightings
- 13
- Last seen by us
- Oct 6, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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