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.
You’ll Work Across: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, 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
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 (i.e., vLLM, Ray, SGLang, Triton)
Our research methodology is grounded in methodical, step-by-step approaches to 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) plan
Relocation and immigration support on a case-by-case basis
In-office snacks and meals provided
Unlimited PTO and company holidays
In-person team in San Francisco with a collaborative, high-energy environment
Skills Required
- Experience in high-performance compute environments such as ML clusters or GPU farms and hyperscaler cloud environments including AWS or GCP
- Experience with infrastructure as code, such as Terraform or Ansible
- Familiarity with containers such as Docker or Apptainer and scheduling systems such as Kubernetes or Slurm
- Experience managing runbooks, disaster recovery planning, change management, and fault tolerance
- Experience with deployment strategies at scale
- 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
- Prior work supporting ML or AI infrastructure, including GPU management and workload optimization
- Exposure to backend development for ML model serving using technologies such as vLLM, Ray, SGLang, or Triton
- Familiarity with software release engineering for ML or AI systems
What We Do
Zyphra is a full stack AGI company based in Palo Alto, California.
