Machine learning engineer • lugano
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About the job 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.
This is a Hybrid (work from home & office) position.
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