MLOps Engineer

Description

Job Summary: We are seeking an MLOps Engineer consultant to design and implement scalable cloud architectures on AWS and AI solutions, leading technical standards and the team's roadmap. Key Highlights: 1. Design and implementation of scalable cloud architectures on AWS for AI. 2. Technical leadership, mentoring, and definition of standards. 3. Use of modern MLOps tools such as Terraform, Kubernetes, and Airflow. At Timestamp, we are looking for an MLOps Engineer consultant to join one of our projects. You will participate in designing and implementing a scalable and distributed cloud architecture, primarily on AWS, focused on Artificial Intelligence solutions. **Responsibilities** * Design and implementation of scalable cloud architectures on AWS. * Deployment of MLOps solutions using Infrastructure-as-Code (Terraform). * Design and evolution of MLOps frameworks for AI model training, deployment, and inference. * Standardization of code templates (PySpark, FastAPI, Streamlit). * Improvement of self-service experience for Data Science teams (repositories, pipelines, and automated infrastructure). * Definition of the execution stack: + PySpark with Airflow (orchestration) and Databricks (computation). + FastAPI and Streamlit services with Helm, GitOps (ArgoCD), and Kubernetes (on\-premise / EKS). * Design of cloud cost control and scalability strategies. * Leadership of technical standards and cross-cutting methodologies. * Definition and tracking of the team's roadmap (Agile methodology). **Requirements** * 3–5 years of experience in designing and implementing MLOps solutions. * Experience with Kubernetes (application deployment and automation). * Experience with modern MLOps tools and practices: + Jenkins, ArgoCD, GitOps, Airflow, MLflow, Terraform, Helm. * Experience with AWS (infrastructure, automation, and security). * Experience with Databricks (data and ML pipelines). * Ability to define technical standards and make architectural decisions. * Experience in technical leadership and mentoring teams. * Intermediate/advanced level of English (mandatory). **Preferred Qualifications** * Certifications: + AWS Solutions Architect (Associate or Professional) + Certified Kubernetes Administrator (CKA)