Machine Learning Engineer

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

Job summary

Discovered MENA in Abu Dhabi is seeking an on-site AI/ML Engineer to design and develop scalable models and AI-driven solutions that address complex business challenges and improve decision-making.

You will work with large data sets, train and deploy ML/DL/NLP/CV models, fine-tune LLMs, and collaborate with cross-functional teams to deliver end-to-end solutions. Relocation to Abu Dhabi is required.

Qualifications

• 3–7 years of production-grade AI system experience.
• Expert in ML domains: supervised/unsupervised learning, NLP, CV, or generative AI.
• Strong ML system architecture and deployment knowledge.
• Experience with API development (FastAPI, Flask) and model optimization.
• Familiar with Docker, Kubernetes, CI/CD, and MLOps tools.
• Experience deploying on AWS or Azure.
• Bachelor’s degree in CS/Engineering; Master/PhD preferred.

Responsibilities

• Work with large data sets to solve business problems.
• Train and deploy ML, NN, and agentic models.
• Develop and optimize models with state-of-the-art algorithms.
• Automate model training, testing, and deployment using CI/CD and MLOps.
• Collaborate with cross-functional teams to deliver end-to-end solutions.
• Fine-tune LLMs and build complex AI architectures.

Skills

ML systems design

Supervised/unsupervised learning

Deep learning

NLP

Computer vision

Generative AI

ML model serving

API development

Docker

Kubernetes

CI/CD

MLOps

AWS/Azure

Education

Bachelor’s degree in CS/Engineering

Master or PhD preferred

Tools

MLflow

Kubeflow

FastAPI

Flask

Docker

Kubernetes

CI/CD tooling

Job description

This position is on site in Abu Dhabi, relocation is required.

In this position you will design and develop scalable machine learning models and AI-driven solutions to address complex business challenges and enhance decision-making processes.

Key Responsibilities

• Work with large and complex data sets to solve challenging business problems.
• Efficient training and deployment of standard ML, NN, and Agentic models.
• Develop, train, and optimize machine learning models using state-of-the-art algorithms and
• frameworks.
• model training, validation, and deployment.
• Automate workflows for model training, testing, and deployment using CI/CD pipelines and
• MLOps tools.
• Collaborate with cross-functional teams to integrate models into applications and deliver
• end-to-end solutions.
• Finetune SLMs/LLMs and build complex AI architectures.

Qualifications / Experience

• (3-7) years of experience in building production grade, scalable AI systems.
• Expert in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).
• Strong ML system architecture skills.
• Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.
• General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps).
• Comfortable with deploying models on AWS or Azure.
• Minimum Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required.
• Preferred Education qualifications: Master or PhD in Computer Science or a related field