mlops engineer

Verisure is a company operating in the manufacturing industry.

• Design, maintain, and evolve the AIOps platform supporting traditional machine learning models, LLM-based solutions, and speech analytics use cases;
• Build and operate ML and LLM pipelines with a focus on reliability, automation, observability, model quality, performance monitoring, and cloud cost optimization;
• Implement LLMOps and AgentOps practices including LLM evaluation, prompt management, traceability, and agent orchestration;
• Ensure continuous operation of AI products through alerts, dashboards, SLOs/SLIs, and scalability strategies;
• Manage deployments in cloud environments and container platforms;
• Collaborate with Data Scientists and Data Engineers to productionize AI solutions;
• Contribute to internal standards, automation, and best practices across the AI and data ecosystem.

• Hands-on experience in MLOps, AIOps, or operating ML systems in production;
• Solid understanding of LLMOps and AgentOps concepts;
• Experience working with AWS and/or Azure in production environments;
• Practical knowledge of containers and Kubernetes;
• Experience with CI/CD pipelines;
• Familiarity with observability and monitoring concepts;
• Experience managing infrastructure as code;
• Python experience and familiarity with the ML ecosystem;
• Good understanding of the ML/LLM lifecycle;
• Fluent English;
• Nice to have: Experience with ML/AI platforms (SageMaker, Azure ML, MLflow, Kubeflow), exposure to Speech Analytics technologies, experience with cloud cost optimization/FinOps, experience building or operating AI agents, familiarity with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel), experience with workflow and orchestration tools.

• No conditions specified