[AI Research Div.] AI Infra Engineer Lead (8년 이상)

The role

This senior engineer will operate and advance large-scale GPU infrastructure. They will design and manage Kubernetes-based ML/GPU platforms and propose computing infrastructure expansion strategies.

What you will do

• Operate and advance large-scale Blackwell Ultra based GPU infrastructure
• Design, build, and operate Kubernetes-based ML/GPU platform scheduling, multi-tenancy, workload isolation, quota, observability, and fault response systems
• Establish and reflect operational strategies to improve GPU utilization, latency, throughput, and cost efficiency
• Propose technical reviews for future computing infrastructure expansion and external infrastructure utilization based on GPU capacity planning
• Advance reproducible operational systems based on GPU and coordinate requirements from multiple teams

Required qualifications

• Experience designing, building, and operating large-scale GPU clusters or Kubernetes/Slurm based AI/ML infrastructure
• Experience understanding computing infrastructure including GPU servers, networks, and storage and building stable operational environments
• Experience applying GPU resource management, scheduling, multi-tenancy, workload isolation, and quota to operational environments
• Experience optimizing infrastructure by analyzing GPU utilization, performance, stability, and cost
• Experience analyzing failures and performance issues from a system perspective to perform root cause resolution and structural improvement
• Experience collaborating with research, development, and service organizations to define infrastructure requirements and propose/execute expansion and operation directions
• No disqualification for overseas business trips

Nice to have

• Experience establishing and reflecting GPU infrastructure cost and performance optimization strategies
• Experience defining infrastructure requirements and proposing technical alternatives and execution priorities in collaboration with research, development, and service organizations
• Experience reviewing and executing computing infrastructure expansion strategies including on-premises, cloud, and external infrastructure
• Understanding of the entire ML workflow including model training, experiment, deployment, inference, and serving
• Experience building repeatable and efficient infrastructure operation systems using IaC, automation, CI/CD, and observability tools
• Experience increasing operational efficiency and automation productivity using Generative AI, LLM-based tools, and code assistants

Before you apply

• Hiring may close early upon completion of recruitment
• Interviews and job tests may be added if necessary
• A 5-month probationary period applies
• Employment may be terminated based on evaluation results during the probationary period

About the company

KRAFTON pioneers the path to players' dreams with bold imagination and breakthrough technology to create unforgettable worlds.