Machine Learning Engineer – Abu Dhabi

DISCOVERED; Abu Dhabi; On-site; AED 250,000 - 400,000; Full time

Job summary

DISCOVERED is seeking a highly technical Machine Learning Engineer in Abu Dhabi to build and deploy scalable AI systems across the full ML lifecycle. This hands-on role focuses on production engineering, model development, training, deployment and integration into live applications.

You will work with traditional ML, deep learning, NLP, CV and Generative AI architectures, fine-tune LLMs, and implement CI/CD with MLOps to automate training and deployment.

Qualifications

• 3–7 years of experience building and deploying production-grade ML systems.
• Hands-on expertise across ML including deep learning, NLP, Computer Vision or Generative AI.
• Strong understanding of ML architecture from development to production.
• Experience with LLMs, fine-tuning and modern AI architectures.
• Experience with model serving and API development (FastAPI/Flask).
• Knowledge of Docker, Kubernetes, CI/CD and MLOps tools (MLflow, Kubeflow).
• Experience deploying ML models on AWS or Azure.
• Bachelor’s degree in CS/Engineering; Master’s/PhD advantageous.

Responsibilities

• Design, train and deploy production-grade ML/AI models across complex use cases.
• Build end-to-end ML pipelines for ingestion, transformation, training, validation, deployment and optimisation.
• Work with traditional ML, deep learning, NLP, CV or Generative AI architectures.
• Fine-tune LLMs/SLMs and contribute to Generative AI solutions.
• Automate training, testing and deployment using CI/CD and MLOps.
• Build scalable model serving for real-time and batch inference.
• Collaborate with Software, Data and AI teams to integrate models into production apps.

Skills

Machine Learning

Deep Learning

NLP

Computer Vision

Generative AI

MLOps

CI/CD

Docker

Kubernetes

API development

Education

Bachelor's in CS/Engineering

Master's or PhD

Tools

FastAPI

Flask

MLflow

Kubeflow

Docker

Job description

Job description

Discover the Opportunity

We’re partnering with a leading financial services organisation in Abu Dhabi that is continuing to expand its AI and Machine Learning capabilities.

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.