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Inferact, founded by the creators and core maintainers of vLLM, is seeking a Member of Technical Staff in Cloud Orchestration to build the operational backbone for vLLM as the world's AI inference engine. In this role, you will design and implement systems for cluster management, deployment automation, and production monitoring that enable teams globally to serve AI models at scale without friction.
You will own the infrastructure that makes vLLM deployments observable, debuggable, and recoverable—turning operational complexity into reliable systems. This includes designing custom Kubernetes operators, managing GPU clusters at massive scale, and ensuring multi-cloud and on-premise deployments work seamlessly across AWS, GCP, Azure, and private infrastructure.
Key responsibilities include architecting cluster orchestration solutions, implementing infrastructure-as-code for reproducible deployments, debugging hardware and software issues in production GPU environments, and collaborating across teams to improve operational reliability for ML inference systems.
Required qualifications: Bachelor's degree in computer science, engineering, or equivalent; strong hands-on experience with Kubernetes and container orchestration at production scale; experience designing and implementing custom Kubernetes operators; proficiency in Python, Rust, or Go; expertise with infrastructure-as-code tools (Terraform, Helm); and experience managing GPU clusters and debugging hardware issues.
Preferred: experience with ML-specific orchestration tools (Ray, Slurm), knowledge of GPU scheduling and multi-tenancy, familiarity with vLLM deployment patterns, and a track record of improving operational reliability for ML systems. Bonus: experience deploying inference systems on large-scale GPU clusters (1,000+ GPUs).
Fully remote, worldwide, with timezone flexibility but expectation of regular overlap with Pacific Time for critical syncs. Competitive salary and equity. Visa sponsorship available on a case-by-case basis.
