AI Engineer
Looking for an AI Engineer to Develop, deploy, and operate AI/LLM models across Clinets dual environment — GCP for public-cloud workloads, Humain sovereign cloud for classified data.
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
Skills
As published by workable · 3 questions · 1 written answer
Basics
First name, Last name, Email, Phone, Photo, Education, Experience, Summary, Resume, What's your expected monthly salary in SAR must?, What's your current monthly salary in SAR must?
Short answers (2)
- What's your Nationality and current resident location
- What's your Total years of relevant Work experience
Written answers (1)
- What's your Notice Period Days to join