AI Engineer
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Key skills for this role
Key Skills for This Role
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Requirements
- Build and fine-tune LLM/ML models for Arabic NLP, document classification, vision/OCR, and AIOps use cases.
- Run pre-deployment evaluation
- Accuracy baselines, regression and safety testing; evidence to justify GPU allocation.
- Optimize inference — quantization, batching, context sizing — against measured usage.
- Deploy on Humain GPUaaS: Kubernetes, GPU partitioning on B300 nodes, quotas, RBAC.
- Build equivalent workloads on GCP (Vertex AI, GKE) with classification-based routing.
- Own serving stack (vLLM/TGI), model versioning, CI/CD, and monitoring for latency, tokens, GPU utilization, and drift.
- Ensuring developed AI Models Complying with ZATCA data sovereignty and SDAIA requirements (AI Ethics, GenAI Guidelines, PDPL).
Benefits
- 5 years ML/AI engineering, in production LLM deployment with knowledge in
- Python, PyTorch, Hugging Face
- Kubernetes in production; GPU-served inference
- GCP Vertex AI or any equivellent cloud
About InnovationTeam
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