Machine Learning Engineer

Client of Discovered MENA; Abu Dhabi; On-site; AED 240,000 - 480,000; Full time

Job summary

Client of Discovered MENA in Abu Dhabi seeks a highly technical hands-on Machine Learning Engineer to build and deploy scalable AI systems across the full ML lifecycle, from model development to production integration.

You will design, train, and deploy production-grade models, implement end-to-end ML pipelines, fine-tune LLMs, and automate through CI/CD and MLOps to deliver real-time and batch inference in live applications.

Qualifications

• 3–7 years building production-grade AI/ML systems.
• Experience across ML, DL, NLP, CV or Generative AI.
• Understanding of ML architectures from dev to production.
• Experience with LLMs and model fine-tuning.
• Experience deploying models via API using FastAPI/Flask.

Responsibilities

• Design, train, and deploy production-grade ML models across use cases.
• Build end-to-end ML pipelines for data ingestion, transformation, training, validation, deployment.
• Automate training, testing, and deployment with CI/CD and MLOps.
• Develop scalable model serving for real-time and batch inference.
• Collaborate with Software/Data/AI teams to integrate models into live apps.

Skills

ML engineering

Deep learning

NLP

Computer Vision

Generative AI

ML Ops

API development

Education

Bachelor's degree in CS/Engineering

Master's or PhD advantageous

Tools

Docker

Kubernetes

CI/CD tools

MLflow/Kubeflow

Job description

nbsp They re looking for a highly technical hands-on Machine Learning Engineer to build and deploy scalable AI systems that solve complex real-world business problems This role is heavily focused on production engineering You ll work across the full ML lifecycle from model development and training through to deployment optimisation and integration into live applications

Discover the Responsibilities

• Design train and deploy production-grade Machine Learning and AI models across a range of complex use cases
• Build end-to-end ML pipelines covering data ingestion transformation training validation deployment and ongoing optimisation
• Work with traditional ML deep learning neural networks and emerging Agentic AI architectures
• Fine-tune LLMs SLMs and contribute to the development of more complex Generative AI solutions
• Automate model training testing and deployment through CI CD and modern MLOps practices
• Build scalable model serving capabilities for both real-time and batch inference
• Work closely with Software Data and AI teams to integrate models into production applications

Discover the Requirements

• 3 7 years of experience building and deploying production-grade, scalable AI/ML systems.
• Strong hands‑on expertise across Machine Learning, with experience in areas such as deep learning, NLP, Computer Vision or Generative AI.
• Strong understanding of ML system architecture and taking models from development through to production.
• Experience with LLMs, model fine-tuning and modern AI architectures.
• Experience with model serving and API development using technologies such as FastAPI or Flask.
• Understanding of Docker, Kubernetes, CI/CD and MLOps tooling such as MLflow or Kubeflow.
• Experience deploying Machine Learning models across AWS or Azure.
• Bachelor s degree in Computer Science, Engineering or a related technical discipline; Master s or PhD would be advantageous.