Devops Engineer
San Francisco; New York Full time On-site Engineering As a Member of Technical Staff, Infrastructure Engineer, you'll play a key role in designing, scaling, and operating the core platform infrastructure that powers autonomous scientific
Location
San Francisco; New York
Employment Type
Full time
Location Type
On-site
Department
Engineering
Compensation
The Role
As a Member of Technical Staff, Infrastructure Engineer, you'll play a key role in designing, scaling, and operating the core platform infrastructure that powers autonomous scientific discovery.
Our mission is to build an AI scientist, and you'll own the infrastructure foundation it runs on. AI agents performing long-running scientific research demand resilient scheduling, lifecycle management, and resource orchestration far beyond typical cloud-native workloads. This role will establish infrastructure best practices, and partner closely with backend engineers, ML engineers, and researchers to deliver a production-grade environment that lets science move faster.
At Edison Scientific, engineering at the senior level is about technical ownership and leverage- understanding how complex systems interact, making sound architectural tradeoffs, and building foundations that allow teams and science to move faster.
This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.
This position is part of the Platform team.
Responsibilities
Architect, implement, and operate Kubernetes clusters that support thousands of concurrent, persistent resources (agents, jobs, services) with high availability and efficient resource utilization.
Drive the strategy for cluster scaling, node pool management, autoscaling policies, and resource quota frameworks to handle rapid workload growth.
Design and implement robust scheduling, placement, and affinity strategies to optimize cost, performance, and fault tolerance for heterogeneous workloads (CPU, GPU, memory-intensive).
Establish and uphold best practices around observability, monitoring, alerting, and incident response for infrastructure systems (Prometheus, Grafana, Datadog, or similar).
Own storage and networking strategy within Kubernetes — including persistent volume management, CSI drivers, service mesh, network policies, and ingress architecture.
Troubleshoot complex, cross-system infrastructure issues and guide others through effective debugging and remediation in distributed environments.
Collaborate closely with backend, ML, and research teams to understand workload requirements and translate them into reliable infrastructure patterns.
Qualifications
Typically, 5+ years of professional infrastructure or platform engineering experience, with hands-on Kubernetes experience in production environments.
Posted July 28, 2026