The future of intelligence is open.
About the role
As a Platform Engineer , you’ll be responsible for designing and maintaining the systems that keep Zyphra’s infrastructure robust, observable, secure, and scalable. Your work will be essential to ensuring the reliability and reproducibility of ML workloads, the safety and control of deployments, and the long-term maintainability of our compute environments.
What they're looking for
- Experience in high-performance compute environments, such as ML clusters or GPU farms as well as hyperscaler cloud environments (i.e. AWS, GCP, etc.)
- Background in infrastructure as code (i.e., Terraform, Ansible, etc.)
- Familiarity with containers (i.e., Docker, Apptainer) and their integration with scheduling systems (i.e., Kubernetes, Slurm)
- Familiarity with software release engineering for ML/AI systems is a plus
- Experience managing run-books, DRP, change management, and general fault tolerance
- Experience with deployment strategies at scale
More about this role
As a Platform Engineer , you’ll be responsible for designing and maintaining the systems that keep Zyphra’s infrastructure robust, observable, secure, and scalable. Your work will be essential to ensuring the reliability and reproducibility of ML workloads, the safety and control of deployments, and the long-term maintainability of our compute environments.
Building and improving observability systems (monitoring, logging, alerting)
Managing Infrastructure as a Service across the stack along with CI/CD in close partnership with engineering teams
Designing resilient build and deployment systems across research and production environments
Implementing secure release processes with strong auditability and rollback support
Collaborating closely with ML engineers, DevOps, and infra teams to improve system reliability and performance
Leading incident response, root-cause analysis, and postmortems with a focus on learning and prevention
This role is ideal for someone who loves building systems that make other teams faster, safer, and more productive
Experience in high-performance compute environments, such as ML clusters or GPU farms as well as hyperscaler cloud environments (i.e. AWS,...
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