Senior DevOps Engineer

About Immunai: Immunai is an AI-driven platform company focused on improving drug discovery and development by decoding the human immune system. We combine large-scale single cell immune data, advanced machine learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process. Our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. We’re building this platform thoughtfully and collaboratively, bringing together expertise across biology, AI, engineering, and business. Immunai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. As a Senior DevOps Engineer, you will join our data & engineering team and design and manage scalable, cloud-based infrastructure focused on big data and machine learning. You will ensure high-scale production environments are reliable, secure, and efficient, supporting seamless ML/AI deployments. Location: Ramat Gan, Israel (hybrid model) Reporting to: DevOps Team Lead What will you do? Design, build, and maintain scalable and reliable infrastructure for our big data applications Automate the deployment and scaling of our applications using Kubernetes and related technologies. Set up, operate, and maintain Kubernetes-based environments, including GKE clusters and Helm-based deployments. Support deployment workflows for PyTorch and TensorFlow-based ML/AI workloads. Support and optimize GPU cluster infrastructure for machine learning workloads. Build and maintain CI/CD pipelines using tools such as GitHub Actions. Set up and maintain deployment environments for ML services and infrastructure components. Work with MLOps platforms, including ClearML, to support experiment tracking, orchestration, and production workflows. Manage cloud infrastructure on GCP with attention to reliability, scalability, cost awareness, and security. Build and maintain cloud networking and security configurations. Implement observability and monitoring using tools such as Grafana, Loki, and Prometheus. Collaborate with DevOps, ML, data, and engineering teams to improve platform reliability and developer experience.