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Senior AI Engineer / AI Architect Engineer

Systems Limited

Abu Dhabi

On-site

AED 120,000 - 200,000

Full time

Today
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Job summary

A technology solutions provider is seeking experienced candidates with over 6 years in AI, machine learning, and data science. The role involves deploying models using Kubernetes and optimizing performance. Proficiency in Python and cloud platforms is essential. Ideal for those with a track record of delivering impactful solutions. Located in Abu Dhabi, UAE.

Qualifications

  • 6+ years of experience in AI, machine learning, or data science.
  • Hands-on experience deploying and scaling machine learning models using Kubernetes.
  • Proficiency in Python and common ML/Data Science libraries.

Skills

AI experience
Machine learning
Data science
Kubernetes
Model optimization
Python
Cloud platforms (AWS, Azure, GCP)
Job description

Looking for candidates available in UAE only.

Interview mode - Face to Face.

JD:

Technical & Functional Skills
  • 6+ years of experience in AI, machine learning, or data science, with a proven track record of delivering high-impact solutions. Leadership or mentorship experience is highly valued.
  • Hands-on experience deploying and scaling machine learning models in production using Kubernetes, with a focus on performance and reliability.
  • Experience with optimizing model serving, including GPU inferencing and framework-specific performance tuning.
  • Deep understanding of model evaluation techniques, A/B testing, and AI explainability methods (e.g., SHAP, LIME).
  • Proficiency or experience with AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code).
  • Experience with automated testing frameworks (e.g., pytest, unittest, pydantic) and CI/CD practices for machine learning.
  • Expertise in designing or utilizing Knowledge Graphs, with experience in graph databases such as TigerGraph or Neo4j.
  • Familiarity with Reinforcement Learning (RL) concepts and their practical application.
  • Proficiency in Python and common ML/Data Science libraries (e.g., scikit-learn, pandas, PyTorch, TensorFlow).
  • Experience with LLMs, NLP techniques, and agentic frameworks (e.g., LangChain, CrewAI, Microsoft Agentic Framework, MCP, A2A).
  • Strong experience with cloud platforms (AWS, Azure, or GCP).
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