More jobs:
AI Infrastructure Consultant
Job in
Riyadh, Riyadh Region, Saudi Arabia
Listed on 2026-02-27
Listing for:
Yallo Retail
Seasonal/Temporary
position Listed on 2026-02-27
Job specializations:
-
IT/Tech
AI Engineer, Cloud Computing, Systems Engineer, Data Engineer
Job Description & How to Apply Below
Job Title: AI Infrastructure Consultant
Job Type: Permanent
Job Location: Riyadh, Saudi Arabia
Job Summary:We are seeking a seasoned AI Infrastructure Consultant to lead the design, implementation, and optimization of our high-performance computing environment. This role is critical for bridging the gap between raw hardware capabilities (GPUs) and scalable AI/ML model deployment. You will be responsible for ensuring our infrastructure is robust, cost-effective, and capable of supporting complex machine learning workloads at scale.
Roles and Responsibilities:- Assess AI/ML workload requirements to design end-to-end compute, storage, and networking architectures.
- Architect specialized GPU clusters (NVIDIA A100/H100 or similar) tailored for training and inference.
- Define high-speed networking requirements (e.g., Infini Band, RoCE) and low-latency storage solutions for massive datasets.
- Implement and manage Docker containerization for consistent model environments.
- Deploy and scale AI workloads using Kubernetes (or managed services like EKS/GKE/AKS), ensuring high availability and seamless resource scheduling.
- Build and maintain robust CI/CD pipelines specifically for AI models, automating the journey from code to production.
- Integrate automated testing, versioning for models/data, and deployment strategies (Canary, Blue-Green).
- Establish comprehensive monitoring frameworks to track infrastructure utilization and GPU health.
- Analyze performance bottlenecks and implement strategies to optimize cost-performance, ensuring maximum ROI on expensive compute resources.
Qualifications & Skills:
- Total
Experience:
10+ years in IT Infrastructure, Systems Engineering, or Dev Ops. - AI Specialization: 2–3 years of hands‑on experience specifically in AI/ML infrastructure.
- GPU Expertise:
Proven track record in GPU setup, CUDA configurations, and managing hardware acceleration for deep learning. - Orchestration:
Expert‑level knowledge of Kubernetes and the CNCF ecosystem. - Cloud & Hybrid:
Proficiency in major cloud providers (AWS/Azure/GCP) and on‑premise data center environments. - Soft Skills:
Strong consultancy mindset with the ability to translate complex technical requirements into actionable architectural roadmaps.
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