AI Engineer
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Key skills for this role
Role Overview
The employer is seeking an AI Engineer to develop, deploy, and operate AI and LLM models across GCP and a sovereign cloud environment.
The role supports public-cloud workloads and classified-data workloads in separate environments.
Key Skills for This Role
Full Job Posting
Role Overview
The employer is seeking an AI Engineer to develop, deploy, and operate AI and LLM models across GCP and a sovereign cloud environment.
The role supports public-cloud workloads and classified-data workloads in separate environments.
Responsibilities
- Build and fine-tune models for Arabic NLP, document classification, vision and OCR, and AIOps use cases.
- Run pre-deployment accuracy, regression, and safety evaluations and provide evidence for GPU allocation.
- Optimize inference through quantization, batching, and context sizing based on measured usage.
- Deploy GPU workloads using Kubernetes, GPU partitioning, quotas, and role-based access control.
- Build equivalent GCP workloads with Vertex AI and GKE using classification-based routing.
- Own vLLM or TGI serving, model versioning, CI/CD, and monitoring for latency, token usage, GPU utilization, and drift.
- Ensure developed AI models comply with ZATCA and SDAIA requirements, AI ethics guidelines, generative AI guidelines, and PDPL.
Requirements
- Approximately 5 years of machine learning or AI engineering experience.
- Production experience deploying large language models.
- Knowledge of Python, PyTorch, and Hugging Face.
- Production Kubernetes experience with GPU-served inference.
- Experience with GCP Vertex AI or an equivalent cloud platform.
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