ML Systems Engineer: Production AI & Scalable Pipelines

Client of Discovered MENA; Abu Dhabi; On-site; AED 400,000 - 640,000; Full time

Job summary

Client of Discovered MENA is seeking a Machine Learning Engineer in Abu Dhabi to design, build and deploy scalable ML systems across the organisation. You will work on the full ML lifecycle—from data handling and model training to validation, deployment and optimisation in production.

You will apply traditional ML, deep learning, NLP and generative AI approaches, building end-to-end pipelines and automating training and deployment workflows while collaborating with Data Science, Engineering and

Qualifications

• 3–7 years of experience building scalable, production-grade AI or ML systems.

Responsibilities

• Design, build and deploy scalable ML systems for real business problems across the organisation.
• Cover full ML lifecycle from data handling to model training, validation, deployment and optimisation in production.
• Work with traditional ML, neural networks, generative AI and agentic systems where appropriate.
• Build end-to-end ML pipelines and automate training and deployment workflows.
• Collaborate with Data Science, Engineering and Product teams to integrate models into applications.
• Ensure models work beyond prototypes, fine-tuning LLMs/SLMs and building model-serving APIs for real-time and batch inference.

Skills

AI systems

Deep learning

NLP

Generative AI

Computer vision

Model serving

API development

Docker

Kubernetes

CI/CD

MLOps

AWS

Azure

Education

Bachelor's degree in CS/Engineering

Master's degree or PhD in CS/AI

Tools

FastAPI

Flask

Docker

Kubernetes

MLflow

Kubeflow

AWS

Azure

Job description

Client of Discovered MENA is seeking a Machine Learning Engineer in Abu Dhabi to design, build and deploy scalable ML systems across the organisation. You will work on the full ML lifecycle—from data handling and model training to validation, deployment and optimisation in production.

You will apply traditional ML, deep learning, NLP and generative AI approaches, building end-to-end pipelines and automating training and deployment workflows while collaborating with Data Science, Engineering and