Jobs / Storm Group
LLMOps / MLOps Engineer – H/F
Storm Group · Paris, A8, France
Paris, A8, FranceExp: 3-5 yrs50,000-60,000 EUR/yearlyRemote
Remuneration
75% public transport reimbursement; meal vouchers covered at 50% (€10.50 per day); sports and wellness access; health and disability insurance; Udemy Business; referral, profit-sharing, and participation bonuses.
Location
Paris, A8, France
Visa sponsorship
Not specified
Job summary
The LLMOps / MLOps Engineer industrializes generative AI and agentic systems for production by designing, deploying, and securing cloud platforms, automation pipelines, and inference environments. The role builds infrastructure with Terraform across Azure, AWS, or GCP; deploys workloads on Docker, Kubernetes, or OpenShift; and establishes CI/CD and GitOps workflows, model observability with MLflow, secure access, high availability, and AI FinOps practices.
Benefits
75% public transport reimbursementMeal vouchers covered at 50% (€10.50 per day)Sports and wellness accessHealth and disability insuranceUdemy Business training accessReferral, profit-sharing, and participation bonuses
Qualifications
- Three to five years of DevOps or cloud engineering experience, including hands-on deployment and industrialization of MLOps or LLMOps solutions.
- Proficiency with a major cloud environment—Azure, AWS, or GCP—and Terraform.
- Strong containerization and orchestration experience with Docker, Kubernetes, or OpenShift.
- Proficiency in CI/CD pipelines and GitOps or DevSecOps practices.
- Operational knowledge of ML and LLM lifecycles, including MLflow, LLM gateways, model APIs, and vector databases.
- Awareness of AI FinOps and inference monitoring.
- Professional working proficiency in English.
Responsibilities
- Design and implement the target architecture for an AI platform using Terraform and Infrastructure as Code principles.
- Deploy, configure, and administer cloud environments on Azure, AWS, or GCP and container clusters on Kubernetes or OpenShift.
- Build and industrialize CI/CD and GitOps pipelines for AI components and foundation models.
- Integrate language models, LLM gateways, agent orchestrators, cognitive service APIs, and vector databases.
- Implement security controls, identity and access management, and centralized secrets management.
- Deploy and oversee observability, logging, and model performance monitoring, including latency and drift dashboards.
- Ensure production inference environments are robust, scalable, and highly available.
- Manage infrastructure and model-call costs through AI FinOps practices.
- Maintain architecture reversibility, maintainability, and technical documentation.
Skills
AWSAzureDockerGCPIAMKubernetesOpenShiftTerraform
Degrees
Engineering degree or university degree at Bac+5 level in computer science, soft
Languages
English
Industry
Generative artificial intelligence
Relocation
No