Member of Technical Staff, Principal AI Infrastructure Engineer
Edison Scientific2 months ago
Base Salary
$200k - $350k/yr
Responsibilities
- Architect, implement, and operate Kubernetes clusters supporting thousands of concurrent persistent resources with high availability and efficient utilization.
- Design custom resource definitions and Kubernetes operators for AI agent lifecycles, research pipelines, and long-running compute tasks.
- Drive cluster scaling, node pool management, autoscaling, and resource quota strategies for rapid workload growth.
- Build and maintain reproducible infrastructure as code using Terraform, Pulumi, or similar tools.
- Develop scheduling, placement, and affinity strategies for heterogeneous CPU, GPU, and memory-intensive workloads.
- Establish observability, monitoring, alerting, and incident response practices for infrastructure systems.
- Own Kubernetes storage and networking strategy, including persistent volumes, CSI drivers, service mesh, network policies, and ingress.
- Troubleshoot complex distributed infrastructure issues and guide others through debugging and remediation.
- Partner with backend, ML, and research teams to translate workload requirements into reliable infrastructure patterns.
Requirements
- 10+ years of professional infrastructure or platform engineering experience with deep hands-on Kubernetes expertise in production environments.
- Experience designing and implementing custom resource definitions and Kubernetes operators using frameworks such as Kubebuilder, Operator SDK, or controller-runtime.
- Experience operating and scaling Kubernetes clusters supporting thousands of persistent or long-lived resources.
- Deep understanding of Kubernetes internals, including the API server, etcd, scheduler, controller manager, and kubelet.
- Expertise with AWS EKS, GCP GKE, or Azure AKS and associated networking, storage, and IAM primitives.
- Proficiency in at least one systems or backend programming language for operator development and infrastructure tooling.
- Hands-on experience with Terraform, Pulumi, or Crossplane and GitOps workflows.
- Strong knowledge of container networking, service mesh, network policies, storage, persistent volumes, StatefulSets, RBAC, Pod Security Standards, and secrets management.
- Ability to work autonomously, make sound technical judgments, and drive projects from concept through production.
- Preferred qualifications include experience with data-intensive platforms, scientific computing, or ML/AI infrastructure; startup or small-team experience; and experience scaling systems, teams, or platforms through rapid growth.
Benefits
- Competitive salary and equity.
- Full healthcare coverage with 100% of premiums paid for employees and dependents.
- Yearly new parent stipend and fertility coverage through Carrot.
- Mental health support through Rula.
- 12 weeks of paid parental leave for maternity, paternity, and adoption.
- Yearly employer-funded pet care stipend.
- Pre-tax commuter benefits for transit and parking.
- 401(k) company matching.
- $300 quarterly health and wellness benefit.
- Lunch is provided every day employees are in the office, and dinner is provided when working late.
- Regular team off-sites and company events.
- Full-time employee benefits; the posting indicates work in an office for some meals but does not specify a broader remote or hybrid policy.
Tech Stack
Categories
About Edison Scientific
Edison Scientific builds AI scientist agents and an R&D platform (Kosmos) for pharma, biotech, and materials teams, integrating with organizations’ proprietary data to guide experiments and analysis from discovery through development. Headquartered in San Francisco and privately held, it was spun out of the nonprofit research lab FutureHouse in 2025, and offers enterprise deployments—including bring-your-own-cloud installations—to meet compliance requirements at large research organizations.