As a Machine Learning Infrastructure Engineer - Site Reliability, 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)
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
Background in infrastructure as code (e.g., Ansible, Terraform)
Familiarity with software release engineering for ML/AI systems
Experience designing reliable environments for experimental workloads and reproducible runs
Knowledge of compliance and audit standards in deployment and system security
Experience with load testing, fault injection, and chaos engineering to harden systems under stress
Passion for building tooling that makes infrastructure invisible and reliable for end users
Experience with infrastructure as code (e.g., Ansible, Terraform)
Prior work supporting ML/AI infrastructure, including GPU management and workload optimization
Exposure to backend development for ML model serving (e.g., vLLM, Ray, SGLang)
Experience working with cloud platforms such as AWS, Azure, or GCP
Familiarity with containers (Docker, Apptainer) and their integration with scheduling systems (Slurm, Kubernetes)
Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued
We strongly value new and crazy ideas and are very willing to bet big on new ideas
We move as quickly as we can; we aim to minimize the bar to impact as low as possible
We all enjoy what we do and love discussing AI
Comprehensive medical, dental, vision, and FSA plans
Competitive compensation and 401(k)
Relocation and immigration support on a case-by-case basis
On-site meals prepared by a dedicated culinary team; Thursday Happy Hours
In-person team in Palo Alto, CA, with a collaborative, high-energy environment
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