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VESSL AI

GPU cloud platform for AI workloads

Junior Site Reliability Engineer

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedHybrid

About the Job

Requirements

  • A bachelor's degree or higher in computer science, electronic engineering, AI, or a related major, or equivalent practical experience.
  • At least 2 years of software engineering experience.
  • Understanding of Linux systems and troubleshooting experience.
  • Experience writing automation scripts or tools using languages such as Python or Go.
  • Basic understanding of container orchestration such as Kubernetes and Docker.
  • Experience operating on-premises or public-cloud infrastructure, or equivalent learning or practical experience.
  • Ability to use data to narrow down causes during incidents.
  • Availability to participate in an on-call rotation.

Responsibilities

  • Build an observability stack based on metrics, logs, and traces, and define SLI/SLOs to track platform reliability quantitatively.
  • Participate in the on-call rotation, respond to incidents, and prevent recurrence through root cause analysis and postmortems.
  • Replace repetitive operational toil with automation scripts, pipelines, and infrastructure as code to improve operational efficiency.
  • Participate in the design, operation, and continuous improvement of infrastructure layers including Kubernetes, GPU clusters, and networks.
  • When deploying new infrastructure, define and validate operational requirements for east-west and north-south networking, storage throughput, and BIOS and firmware settings.

Desired Qualifications

  • Experience building or operating commercial training or inference systems based on accelerators such as GPUs, TPUs, or NPUs.
  • Experience operating large-scale GPU scheduling environments based on Slurm or Kubernetes.
  • Experience managing GPU driver and fabric versions in Kubernetes clusters using NVIDIA GPU Operator.
  • Experience building observability stacks such as Prometheus, Grafana, or OpenTelemetry.
  • Experience operating multi-node cluster environments using high-performance networking such as InfiniBand or RoCEv2.
  • Experience using infrastructure-as-code tools such as Terraform or Ansible.

About the Company

VESSL AI

GPU cloud platform for AI workloads

What VESSL AI does: It runs VESSL Cloud, a GPU cloud platform built for AI workloads. It gives teams on-demand access to high-end GPUs (A100, H100, B200, B300, GB200) to run activities like LLM fine-tuning, large-scale model training, and AI inference. How it works: Users launch GPU instances in VESSL Cloud from VESSL’s own data center infrastructure, paying per minute for usage, and using the platform to accelerate AI development without managing physical hardware. How it stands out: It operates its own data center and offers per-minute billing, delivering up to 80% cost savings versus AWS and GCP, focusing specifically on AI workloads rather than general-purpose cloud services. What the goal is: To help AI teams move quickly from idea to production by removing infrastructure overhead and providing scalable, affordable GPU resources for AI work.

Company size
51-200
Company stage
Series A
Total funding
$16.6M
Headquarters
San Francisco, CA
Founded
2020

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