Site Reliability Engineer Intern
DataikuFrance, ParisPosted 7 April 2026
Tech Stack
Job Description
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube .
Internship goal
Enhance the infrastructure and the continuous Integration pipelines of our Cloud Platform and help with the automation process within our Site Reliability Engineering team.
Detailed description
Dataiku Cloud is the SaaS offering of the Dataiku company specialized in AI and Machine Learning. The SRE team is in charge of the reliability and the performance of our infrastructure and the releases of the platform.
The goal of the internship is to be integrated in one of the SRE teams and work on multiple domains of a modern SRE stack: CI/CD pipeline, Infrastructure as Code, Security, Monitoring, … At the beginning of the internship, an onboarding phase with the SREs will let you learn about major tools used in the cloud industry, including Kubernetes, AWS, Grafana, Github Actions, Docker …
Under the supervision and with the support of your tutor, you will directly collaborate with other SRE team members and developers. You will work from our Paris or Nantes offices and have the opportunity to meet all other Dataiku teams. You’ll be an integral part of our team.
Responsibilities
Collaborate with the SRE team to improve and optimize the CI/CD pipeline
Leverage Kubernetes to build and test images in-cluster
Automate our infrastructure processes
Work on reliability and scalability processes
Define metrics and build monitoring dashboards
Stack
Kubernetes
AWS / Azure
Grafana
ArgoCD
Github Actions
Terraform
AI / machine learning
What are you waiting for!
At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page .
Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at:
reasonable-accommodations@dataiku.com
Protect yourself from fraudulent recruitment activity
Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on ide ... (truncated, view full listing at source)
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