Hard requirements (please DO NOT APPLY if you don't match all):

• 3+ years of experience as a DevOps Engineer.
• EU or Swiss nationality/C permit.

Role

• Design, implement, and maintain robust infrastructure to support scalable AI/ML workloads in production.
• Ensure high availability, reliability, and security of Artificialy’s services across cloud and on-prem environments.
• Develop and manage CI/CD pipelines for rapid and safe deployment of software and machine learning models.
• Monitor system health, performance, and resource usage; implement alerting and incident response strategies.
• Automate infrastructure provisioning and configuration management using tools like Terraform, Ansible, or equivalent.
• Collaborate with the Artificialy teams to streamline development workflows and reduce time-to-production.

Required Skills

• Strong Linux systems knowledge and scripting abilities (e.g., Bash, Python).
• Solid experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).
• Familiarity with Infrastructure-as-Code (e.g., Terraform, Ansible, Helm).
• Minimum 2 years work experience in building CI/CD pipelines with tools like GitLab CI, GitHub Actions, Jenkins, or similar.
• Understanding of networking concepts, security best practices, and system monitoring (e.g., Prometheus, Grafana).
• Ability to work autonomously and collaboratively with cross-functional teams (MLOps, AI engineers, software developers).

Desirable Skills

• Experience with hybrid cloud/on-premises environments.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience managing GPU clusters and distributed computing environments.
• Proficiency with log management and incident analysis (e.g., ELK stack, Loki).
• Exposure to AI/ML toolchains and workflows (e.g., MLflow, Weights & Biases, Triton).
• Fluency in Python for tooling and automation.

We offer

• Full-time permanent contract with competitive compensation and opportunities for technical leadership growth.
• Access to cutting-edge hardware and modern DevOps stacks is also provided, along with mentorship and continuous learning in high-impact, production-grade AI systems.