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Inferact

Open-source LLM inference engine with scalability

Cloud Orchestration Engineer - Cloud Orchestration

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree or equivalent experience in computer science, engineering, or a similar field.
  • Strong experience with Kubernetes and container orchestration at scale.
  • Experience designing and implementing custom Kubernetes operators.
  • Proficiency in Python, Rust, or Go and infrastructure-as-code tools such as Terraform and Helm.
  • Experience managing GPU clusters and debugging hardware issues.
  • Ability to work across cloud platforms including AWS, GCP, and Azure, as well as on-premise infrastructure.

Responsibilities

  • Build the operational backbone that keeps vLLM running reliably at massive scale.
  • Design systems for cluster management, deployment automation, and production monitoring that enable teams worldwide to serve AI models.
  • Ensure vLLM deployments are observable, debuggable, and recoverable, and turn operational complexity into reliable infrastructure.

Desired Qualifications

  • Experience with machine-learning-specific orchestration tools such as Ray and Slurm.
  • Knowledge of GPU scheduling, multi-tenancy, and resource optimization.
  • Familiarity with vLLM deployment patterns and configuration.
  • Track record of improving operational reliability for machine learning systems.
  • Experience deploying inference systems on large-scale GPU clusters of 1,000 or more GPUs.

About the Company

Inferact

Open-source LLM inference engine with scalability

Inferact builds AI inference infrastructure centered on vLLM, an open-source large language model inference engine. It offers a managed inference service for enterprises with serverless deployment, observability, troubleshooting, disaster recovery, and multi-tenant Kubernetes scaling. vLLM uses PagedAttention to optimize GPU memory, lowering costs and latency while preserving model quality, and Inferact supports new architectures and hardware under vendor-neutral governance with PyTorch Foundation. The goal is to commoditize AI inference and deliver a production-ready operating layer for the AI stack.

Company size
11-50
Company stage
Seed
Total funding
$150M
Headquarters
San Francisco, CA
Founded
2025

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