Capacity Ops Engineer
Leads global GPU capacity management across acquisition, orchestration, infrastructure automation, and incident response. The role requires 5+ years of experience, deep Kubernetes expertise, production Go or Python skills, and the ability to balance reliability with unit economics.
About the job
Responsibilities
- Lead specialized GPU pods, owning acquisition, orchestration, and maintenance across the asset lifecycle.
- Execute workload migrations and deployment drains while meeting regional and compliance requirements.
- Design and implement a scalable capacity management system supporting a 10x increase in GPU volume.
- Build ROI and unit-economics models for GPU spending and capacity trade-offs.
- Partner with SRE, infrastructure, and forward-deployed engineering teams on operational execution and infrastructure changes.
- Lead responses to capacity-related incidents and outages.
Requirements
- Bachelor's, master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of professional experience in a high-growth environment, preferably at a hyperscaler or specialized GPU provider.
- Deep expertise in Kubernetes, including taints, cordons, node draining, and custom operators.
- Production-level experience with Go or Python.
- Strong financial literacy and ability to model capacity reliability and cost trade-offs.
- High tenacity and a collaborative mindset.
Benefits
- Competitive compensation, including meaningful equity.
- Medical, dental, and vision insurance fully covered for employees and dependents.
- Flexible paid time off and company-wide winter break.
- Paid parental leave.
- Fertility and family-building stipend.
- Company-facilitated 401(k).
Skills
Kubernetes, Go, Python, Multi-Cloud, Gpu Infrastructure, Nvidia Blackwell, Nvidia H100, Custom Operators, Node Draining, Financial Modeling
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