Member of Technical Staff, Cloud Orchestration (Remote)
At a glance
Senior Software Engineering role at Inferact. Remote, United States · full-time · $200,000–$400,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Build cluster management, deployment automation and production monitoring for reliable vLLM operations at scale
- Make deployments observable and easier to debug, then build recovery into the operating systems
- Create infrastructure that helps teams serve AI models without operational friction
What you bring
- A computer science, engineering or similar degree, or equivalent experience
- Strong Kubernetes and container-orchestration experience at scale, including custom operator design and implementation
- Proficiency in Python, Rust or Go, plus infrastructure-as-code tools such as Terraform or Helm
- Experience operating GPU clusters and troubleshooting hardware, across cloud platforms or on-premise infrastructure
Who this fits
This senior role suits an infrastructure engineer focused on Kubernetes, GPU clusters and reliable ML operations. It is fully remote worldwide, with regular overlap expected with Pacific Time for critical syncs. Visa sponsorship is considered case by case.
From the employer
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: Fully remote, worldwide. We're timezone-flexible but expect regular overlap with Pacific Time for critical syncs.
Compensation: We offer competitive compensations (salary + equity) compared to the local market conditions.
Visa sponsorship: We sponsor visas on a case-by-case basis.
Benefits: Inferact offers competitive benefits appropriate to your location, including health coverage where applicable.
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