Remote Position
[Remote] Senior/Staff Backend Engineer - Distributed System
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. Zettabyte is on a mission to make AI compute ubiquitous, seamless, and limitless. They are seeking a Senior/Staff Backend Engineer to build systems that orchestrate GPU clusters for AI workloads, focusing on creating APIs and resource management systems for GPU lifecycle.
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
- Optimize cold starts for model serving and implement efficient model loading strategies
- Collaborate with frontend engineers to expose complex infrastructure through intuitive interfaces
- Leverage AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor IDE, etc.) to boost productivity and code quality
Skills
- 5+ years backend engineering experience with distributed systems
- Strong 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)
- Comfortable working with expensive resources where efficiency directly impacts costs
- Excited about solving novel problems in AI infrastructure (not just another CRUD app)
- Startup mindset—comfortable with ambiguity and rapid iteration
- GPU or HPC cluster management experience
- Understanding of ML/AI workload patterns and requirements
- Experience with high-value resource allocation systems
- Background in performance optimization for compute-intensive workloads
- Familiarity with GPU virtualization and sharing technologies
- Experience building billing or metering systems
Benefits
- Equity based on your experience and skillset
- Hybrid role - 3 days in office, 2 days WFH
Company Overview