[AI Research Div.] Senior MLOps Engineer (8년 이상)
Tasks
- Automate operations
- Collaborate with research development and service teams
- Design and implement Kubernetes based ML GPU platform
- Develop technical alternatives and execution priorities
- Handle incidents and root cause analysis
- Implement scheduling and multitenancy
- Improve GPU performance
- Improve GPU utilization and throughput
- Isolate workloads and enforce quotas
- Operate GPU infrastructure
- Optimize resource efficiency
- Perform capacity planning and utilization analysis
- Recommend GPU and cloud scaling strategy
- Reduce cost and improve performance
- Set up observability and monitoring
- Standardize reproducible platform operations
Perks/Benefits
- N/A
Skills/Tech-stack
CI/CD | Capacity Planning | Deep learning | GPU Compute | GPU scheduling | GitOps | Incident Management | Infrastructure as Code | Kubernetes | Linux | Machine Learning | Monitoring | Multitenancy | Observability | Quotas | Scheduling | Workload isolation | “as-code”
Education
N/A
Roles
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