Senior Backend Engineer - AI GPU Infra & Scheduling

zettabyte-space; United States; Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive salary and equity

Hybrid work model (3 days in office, 2

days WFH

Job summary

Zettabyte is hiring a Backend Engineer to design APIs that expose GPU orchestration and resource management for AI workloads. You will work on scheduling, multi-tenant isolation, and billing systems while collaborating with frontend engineers to create intuitive interfaces.

The role emphasizes efficient GPU utilization, SLA adherence, and handling high-value compute resources in a fast-paced startup environment located in Palo Alto.

Qualifications

• 5+ years backend engineering experience with distributed systems.
• Proficiency in Go, Python, or similar backend languages.
• Experience with resource scheduling, orchestration, and API design (REST, GraphQL, gRPC).
• Understanding of hardware constraints and system optimization.
• Linux systems knowledge and containerization experience (Docker, Kubernetes).
• Startup mindset—comfortable with ambiguity and rapid iteration.

Responsibilities

• Design APIs that abstract complex GPU operations into simple developer experiences.
• Build scheduling algorithms that maximize GPU utilization while ensuring SLA compliance.
• Develop resource management systems for GPU lifecycle—provisioning, allocation, scheduling, and release.
• Create usage tracking and billing systems for GPU-hours, memory usage, and compute utilization.
• Implement monitoring for GPU-specific metrics, health checks, and automatic failure recovery.
• Build multi-tenancy systems with resource isolation, quota management, and fair scheduling.

Skills

Backend engineering

Distributed systems

Go

Python

API design

Linux

Tools

Docker

Kubernetes

Job description

Zettabyte is hiring a Backend Engineer to design APIs that expose GPU orchestration and resource management for AI workloads. You will work on scheduling, multi-tenant isolation, and billing systems while collaborating with frontend engineers to create intuitive interfaces.

The role emphasizes efficient GPU utilization, SLA adherence, and handling high-value compute resources in a fast-paced startup environment located in Palo Alto.