Experteer Overview As an MLOps Engineer, you will design, build, and run production‐grade ML and GenAI infrastructure at scale. You'll work at the intersection of AI, product engineering, and cloud infrastructure to ensure reliable and well‐governed AI workloads. You'll partner with AI scientists and engineers to move models from experiment to production while optimizing performance and costs. This is a hands‐on, platform‐focused role that shapes the AI foundation of Soldo's financial experiences.
Retribuzione / Benefits Design, build and maintain scalable ML and GenAI infrastructure
Productionise AI models and services across training, deployment and inference workflows
Build and optimise CI/CD pipelines for ML systems
Improve reliability, observability and monitoring of AI workloads
Enable reproducible experimentation, model versioning and automated deployment processes
Partner with AI Scientists to accelerate transition from experimentation to production
Optimise infrastructure performance, scalability and operational costs
Support governance,
compliance and security best practices for AI systems
Contribute to the evolution of our AI platform architecture and engineering standards
Drive operational excellence across the ML lifecycle
Responsabilità Strong experience in MLOps, ML Platform Engineering or AI Infrastructure roles
Proven experience deploying and operating ML/AI systems in production environments
Strong Python engineering skills
Strong knowledge and experience with PySpark and Databricks
Solid experience with cloud platforms such as AWS, GCP or Azure
Experience with containerisation and orchestration technologies (Docker, Kubernetes)
Experience building CI/CD workflows for ML systems
Familiarity with ML orchestration and experiment management tools such as MLflow, Kubeflow, Airflow or similar
Experience with monitoring, logging and observability tools
Understanding of distributed systems and scalable backend architectures
Experience working in cross‐fun
📌 MLOps Engineer (Italia)
🏢 Altro
📍 Italia