Cloud Orchestration Engineer

inferact Singapore
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AI Summary

Build the operational backbone for vLLM's massive-scale cloud infrastructure. Design cluster management, deployment automation, and production monitoring systems. Ensure reliable, observable, and recoverable AI model serving across global teams.

Key Highlights
Design cluster management and deployment automation for vLLM at massive scale
Ensure observability, debuggability, and recoverability of AI model deployments
Manage GPU clusters and debug hardware issues across cloud platforms
Key Responsibilities
Design systems for cluster management
Implement deployment automation
Build production monitoring infrastructure
Ensure vLLM deployments are observable and debuggable
Enable recovery of AI model serving systems
Manage GPU clusters and debug hardware issues
Work across cloud platforms (AWS, GCP, Azure) and on-premise infrastructure
Technical Skills Required
Kubernetes Python GPU cluster management
Benefits & Perks
Medical, dental, and vision coverage
Visa sponsorship
SGD 200K - SGD 400K annual salary
Nice to Have
Experience with ML-specific orchestration tools (Ray, Slurm)
Knowledge of GPU scheduling, multi-tenancy, and resource optimization
Familiarity with vLLM deployment patterns and configuration
Track record of improving operational reliability for ML systems
Experience deploying inference systems on large-scale GPU (1,000+) clusters

Job Description


Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware—a position that took years to build.

About The Role

We're looking for an cloud orchestration engineer to build the operational backbone that keeps vLLM running reliably at massive scale. You'll design the systems for cluster management, deployment automation, and production monitoring that enable teams worldwide to serve AI models without friction. You'll ensure that vLLM deployments are observable, debuggable, and recoverable, turning operational complexity into infrastructure that just works.

Skills And Qualifications

Minimum qualifications:

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

Preferred qualifications:

  • Experience with ML-specific orchestration tools (Ray, Slurm).
  • Knowledge of GPU scheduling, multi-tenancy, and resource optimization.
  • Familiarity with vLLM deployment patterns and configuration.
  • Track record of improving operational reliability for ML systems.

Bonus points if you have:

  • Experience deploying inference systems on large-scale GPU (1,000+) clusters.

Logistics

  • Location: This role is based in Singapore.
  • Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is S$200,000 to S$400,000 annually + equity.
  • Visa sponsorship: We sponsor visas on a case-by-case basis.
  • Benefits: Inferact offers a generous benefits package, including medical, dental, and vision coverage.

Compensation Range: SGD 200K - SGD 400K


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