GenAI & HPC Research Support Analyst

KAUST (King Abdullah University of Science and Technology)

Makkah Region

On-site

SAR 180,000 - 300,000

Full time

14 days+
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Job summary

KAUST Supercomputing Lab in Saudi Arabia is seeking an AI/ML Support Analyst to advance Generative AI research and optimize HPC workflows across climate, bioinformatics, CFD, NLP, and multimodal domains.

You will provide expert consultation to researchers, develop scalable AI models, maintain benchmarks, and contribute to governance, security, and knowledge transfer within KAUST's vibrant research community.

Qualifications

  • Bachelor's or master's degree in CS, data science, AI, or related field.
  • Strong ML fundamentals with research background.

Responsibilities

  • Provide user support via phone, email, walk-in, and ticketing for AI/ML inquiries.
  • Develop large-scale Generative AI models on domain datasets.
  • Fine-tune foundation models on domain datasets using advanced optimization.
  • Develop data engineering pipelines to support AI workflows.
  • Design efficient AI workflows for KAUST's HPC environment.
  • Build OCI-compliant, HPC-ready container images (Singularity/Podman).
  • Develop workflows with SLURM and Kubernetes for distributed training/inference.
  • Support governance, training, and knowledge transfer within KAUST research community.

Skills

Python
Machine Learning
PyTorch
TensorFlow
Linux
HPC Workflows
Kubernetes
SLURM
Containerization
Data Engineering
Research Consulting
GenAI

Education

Bachelor's or Master’s in CS/AI

Tools

Singularity
Podman
NVIDIA GPUs
Kubeflow
NVIDIA Triton

Job description

KAUST Supercomputing Lab in Saudi Arabia is seeking an AI/ML Support Analyst to advance Generative AI research and optimize HPC workflows across climate, bioinformatics, CFD, NLP, and multimodal domains.

You will provide expert consultation to researchers, develop scalable AI models, maintain benchmarks, and contribute to governance, security, and knowledge transfer within KAUST's vibrant research community.

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