Responsibilities
- Design and implement versioned provisioning state machines for the full lifecycle of physical hosts and GPU clusters.
- Build declarative self-service APIs and a control plane for requesting, scaling, and tearing down inference clusters.
- Automate self-healing by detecting degraded nodes, draining them, triggering repair or replacement, and restoring healthy capacity.
- Own pipeline reliability through idempotency, retries, rollback, and drift detection.
- Partner with inference and ML platform teams to encode cluster shapes, topology, interconnects, and scheduling constraints.
- Develop typed, tested, versioned infrastructure software and operate and support it in production.
Requirements
- Strong software engineering background in Go, Python, Rust, or a similar language, including writing and testing production software.
- Experience with durable workflow orchestration tools such as Temporal, Cadence, or equivalent.
- Experience building control planes or orchestration systems that model state and reconcile it over time, such as Kubernetes controllers or operators.
- Experience designing event-driven systems using message queues, event streams, or pub/sub systems such as Kafka, NATS, or SQS.
- Experience building internal platforms or APIs for other engineering teams with attention to developer experience.
- Preferred exposure to bare-metal provisioning technologies such as PXE, iPXE, Redfish, IPMI, or BMC; networking fundamentals; or GPU and accelerator infrastructure.
- Preferred experience with GPU cluster software stacks such as NCCL, CUDA, and InfiniBand or RoCE.
- Prior experience at a hyperscaler, GPU cloud, or datacenter-scale infrastructure organization is preferred.
- Systems programming experience in Rust or Go is preferred.
Benefits
- The role is part of Together AI, a research-driven company focused on open and transparent AI systems and AI infrastructure.
- The company offers equal employment opportunity regardless of protected characteristics.
Vacancy posted 19 hours ago
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