Define end-to-end infra for AI/ML workloads (prod & training)
Design multi-cloud and hybrid infra balancing performance, reliability, cost, and vendor flexibility
Architect compute orchestration for GPU and CPU workloads
Design storage for large datasets and low-latency serving
Lead capacity planning and scale ahead of demand
Drive cost optimization and FinOps practices

🎯 Requirements

Think in systems; connect compute, storage, and network
Experience with real-time production and large-scale ML training
Trade-offs among cost, performance, reliability, velocity
Work across bare metal to cloud and container orchestration
Build cost-effective, burstable infra for AI research
Operate at a strategic level while staying technically deep

🎁 Benefits

Medical, dental, vision benefits
Annual wellness stipend
Unlimited PTO
Flexible schedule
Generous parental leave
401(k) plan with company match

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