Customer Deployment Intern
Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026.
About Probabl
Probabl is the Tabular AI company founded by the creators and stewards of scikit-learn. We build Skore, the Tabular AI platform whose agent builds, validates and tracks predictive models with the statistical methodology of the scikit-learn maintainers; Skore Team is its server side, deployed inside the customer's own infrastructure. We steward scikit-learn and its ecosystem (skrub, joblib, imbalanced-learn, fairlearn, skops, hazardous) and contribute to TabICL, the open source tabular foundation model. Our customers are large groups, often in regulated settings where sovereignty and on-premise deployment matter as much as performance.
The internship
You join Probabl's Services team, the applied AI team between our clients and the engineers who build the product, for six months in Paris. Your job: get Skore Hub running inside the IT of banks, insurers, energy and industrial groups, as virtual machines (GCP Marketplace, AWS, Azure) or on their Kubernetes, and plug it into what they already run: identity, networking, a self-hosted MLflow, an enterprise LLM gateway.
Probabl's infrastructure team, in Tech & Product, builds the deployment stack of Skore Hub: Helm charts, marketplace images, deployment guide. The Services team is its customer arm, and this internship sits at that interface: you take the stack into each customer's environment, make it work with what you find there, and bring back what breaks so the next version installs cleanly.
This is not an observation internship. You work with the Deployment Engineer and the Solution Architect on real customer environments rather than lab sandboxes, with a senior engineer alongside you at every step and the infrastructure team one message away.
What you will do
Deploy Skore Team in customer environments: VMs from our GCP Marketplace listing or on AWS and Azure, or Kubernetes with our Helm charts (GKE, EKS, AKS, OpenShift, on-premise), including sizing, storage, backups and upgrades.
Plug it into the enterprise stack: SSO (OIDC), private endpoints, proxies and restricted egress, the customer's self-hosted MLflow, and the LLM gateway that fronts the models the Skore agent may call.
Make it repeatable, with the infrastructure team: Helm and Terraform improvements, marketplace images, reference architectures and runbooks, so the next deployment starts from a better stack.
Answer the customer's infrastructure and security questions on the call, with a senior engineer next to you, not in front of you, and keep deployments healthy once live (upgrades, bounded support).
What you will learn
How enterprise AI actually gets deployed in on-premise, sovereign and regulated settings; cloud and Kubernetes at production grade on real customer clusters; the ML platform stack of large groups (MLflow, LLM gateways, model serving) from the inside; and what it takes to be trusted by a customer's infrastructure team. The Services team is growing, and a successful internship is the natural way into a full-time Customer Deployment Engineer or Solutions Engineer role.
Who we are looking for
A final-year or gap-year student at a leading engineering school, with a taste for infrastructure and systems.
At home on Linux, with Docker, and with at least one of Kubernetes, Terraform or a cloud platform (GCP, AWS, Azure) used beyond a tutorial: a deployment you did yourself, a homelab, a side project.
Solid Python, enough to script an install and debug a stack trace.
You care about things working the second time: documentation, automation, and saying "this is not ready" when it is not.
Comfortable on a call with a customer's platform team, in French and in English.
OpenShift, a marketplace listing, Helm authoring, an identity provider, MLflow or an LLM gateway are a plus, as are open-source contributions and daily use of a coding agent.
Practical details
Team: Services (applied AI and field engineering), reporting to the VP Services, co-founder of Probabl.
Location: Paris.
Duration: 6 months, final-year internship or gap year. Start: flexible.
Compensation: monthly internship stipend (gratification de stage), to be determined.
Languages: English.
Requirements: eligible for a tripartite internship agreement (convention de stage) and authorized to work full-time in France for the entire duration of the 6-month placement. Visa sponsorship is not available.
How to apply
Send your CV, a link to something we can read (GitHub, a homelab write-up, an infrastructure project), and five to ten lines on the most interesting deployment problem you have solved and what you learned. No cover letter.
The process takes about two weeks: a 30-minute call with the VP Services, a short technical case (deploy a small service on Kubernetes or a VM, connect it to an external component and walk us through your choices; about one hour, live or take-home), and a conversation with the Deployment Engineer or the Solution Architect.