
Data Infrastructure Engineer
4 days ago
We are seeking a skilled professional to design, build, and support AI infrastructure that meets business requirements.
- Analyze current AI infrastructure needs and future growth opportunities.
- Design, deploy, and support AI infrastructure with CPU, GPU, middleware, and orchestration tools.
- Configure and manage PFS (Parallel File System) and NFS (Network File System).
- Install and configure libraries and compilers.
Responsibilities include:
- NVIDIA GPU management and Cuda toolkit support.
- Cloud infrastructure management on AWS and GCP.
- Cloud bursting techniques.
- Kubernetes installation and configuration.
Required Skills:
- Operating Systems: Linux (RHEL, CentOS, SuSE)
- Languages: C, C++, bash, Python
- Schedulers and Resource Management: PBS, SLURM, Grid Engine, LSF
- Cluster Management: xCAT, Bright Cluster Manager, War wolf
- Monitoring: Grafana, Nagios, Zabbix, Ganglia
- Compilers and Libraries: GNU, Intel, OpenMPI, Cuda, MPI
- Networking: InfiniBand/ROCE/UFM/Ethernet/DPU
Broad Responsibilities Include:
- Parallel file system management (GPFS, Lustre, Weka, BeeGFS, VAST)
- Benchmarking tools (IOR, Limpack)
- NVIDIA stack management (Nvidia AI Enterprise, RunAi)
- Configuration and troubleshooting of PFS like Lustre/GPFS/WEKA
- Job scheduler installation, configuration, and troubleshooting
- Root cause analysis of cluster issues
- Performance benchmarking of cluster
- Basic knowledge of parallel programming (OpenMPI, MPI)
- Knowledge in GPU orchestration/MIG instance creation
- Scripting and automation (bash, Perl, Python)
- Advanced Linux OS debugging skills
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