Job Summary: We are seeking an MLOps / LLMOps Engineer to lead the industrialization of the AI model lifecycle, transforming experimentation into scalable and robust products. Key Highlights: 1. Lead the industrialization of AI models, including LLMs 2. Serve as the bridge between Machine Learning and DevOps teams 3. Work with cutting-edge AI technologies Job Description: At Experis Argentina, we are looking for an MLOps / LLMOps Engineer to join a global technology company that is establishing its Delivery Center in Buenos Aires. This role is critical to taking Artificial Intelligence models (including LLMs) from experimentation to scalable, robust, and production-ready products. **Employment Terms** Work Mode: Hybrid (1 or 2 days per week) \- CABA Fluent English Employment Relationship: Direct employment with our client **What Will Be Your Mission?** You will serve as the bridge between Machine Learning and DevOps teams, leading the industrialization of the AI model lifecycle. Your focus will include: * Deployment and scalability of ML and GenAI models * Automation of pipelines (CI/CD) * Observability and monitoring (drift, performance, bias) * Building cloud-native architectures **What Will You Do?** * Design and implement CI/CD pipelines for ML/LLM models * Deploy models in production environments using AWS or GCP * Manage infrastructure as code (Terraform / CloudFormation) * Work with containers (Docker, Kubernetes) for scalable deployments * Implement monitoring and observability solutions (Prometheus, Grafana, ELK) * Collaborate with global teams on AI solution development **What Are We Looking For?** **Mandatory Requirements:** * Experience with Cloud (AWS or GCP), SageMaker or Vertex AI * Solid experience in MLOps / model deployment * Knowledge of Docker and Kubernetes * Experience with Terraform or Infrastructure as Code * Proficiency in Python * Experience working with CI/CD pipelines **Desirable:** * Experience with LLMs / GenAI * Knowledge of frameworks such as LangChain * Experience in LLMOps (monitoring hallucinations, drift, etc.) * Familiarity with MLflow, Kubeflow or similar tools * Experience with vector databases