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MLOps & Cloud Engineer
Sin especificarTiempo completoDevOps & SREBiotechnology
Join an engineering team building and maintaining cloud infrastructure for machine learning, data, and production systems. Work with ML, data, and software engineers to bring models and workflows into production.
Responsabilidades
- Build and maintain cloud infrastructure on Microsoft Azure and GCP.
- Support machine learning training, deployment, inference, and monitoring workflows.
- Work with Kubernetes and Docker environments, including GPU workloads.
- Build and improve data and machine learning pipelines.
- Develop infrastructure automation and CI/CD processes.
- Monitor and troubleshoot cloud, machine learning, and data workloads.
- Collaborate with ML, data, and software engineers to bring models and workflows into production.
Requisitos
- At least 2 years of experience in MLOps, cloud or DevOps, platform engineering, or a similar role.
- Hands-on experience with Azure and/or GCP.
- Experience with Kubernetes and Docker.
- Experience with monitoring tools such as Grafana, Prometheus, or Azure Monitor.
- Good Python and Linux skills.
- Familiarity with machine learning workflows, including training and inference.
- Experience with CI/CD, cloud storage, and data pipelines.
Se valora
- Experience with Azure ML, Vertex AI, MLflow, or similar tools.
- Experience with GPU workloads and machine learning infrastructure.
- Experience with Argo Workflows, Terraform, and Helm.
- Experience with PostgreSQL and MongoDB.
- Experience with large-scale data or image-processing pipelines.