Machine Learning Engineer

Primis; Abu Dhabi; On-site; AED 280,000 - 520,000; Full time

Job summary

Primis is seeking a Machine Learning Engineer to design, develop, and deploy scalable ML/AI solutions that tackle complex business challenges and enable smarter decision-making.

You will work on production-grade ML models, end-to-end pipelines, and AI architectures, collaborating with engineering, product, data, and other teams to integrate AI into applications and deliver end-to-end solutions.

Qualifications

• 3–7 years of experience building production-grade, scalable AI/ML systems.
• Strong expertise in machine learning, with experience in deep learning, NLP, CV, or generative AI/LLMs.
• Strong understanding of ML system architecture and productionisation.
• Experience with model serving and API development using FastAPI or Flask.
• Good understanding of Docker, Kubernetes, CI/CD, and MLOps tools such as MLflow or Kubeflow.
• Experience deploying ML models on AWS or Azure.
• Bachelor’s degree in Computer Science, Engineering, or related field.

Responsibilities

• Design, develop, train, and optimise end-to-end ML pipelines (data ingestion, transformation, training, validation, deployment).
• Build production-grade AI/ML models across DL, NLP, CV, and generative AI domains.
• Collaborate with engineering, product, data, and cross-functional teams to deploy AI models in applications.
• Perform model tuning, monitoring, and performance optimisation for real-time and batch inference.
• Automate model training, testing, and deployment via CI/CD and MLOps practices.
• Develop scalable ML system architectures for robust production environments.
• Evaluate and implement best practices for model serving and API interfaces.
• Drive continuous improvement and production-readiness of AI platforms.

Skills

Machine learning

Deep learning

NLP

Computer vision

Generative AI / LLMs

Model serving

API development

MLOps

Close collaboration

CI/CD

Data analysis

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Master’s or PhD in CS/AI (nice to have)

Tools

Docker

Kubernetes

CI/CD

MLflow

Kubeflow

AWS

Azure

Job description

We are looking for a Machine Learning Engineer to design, develop, and deploy scalable machine learning and AI solutions that solve complex business challenges and support smarter decision-making.

What You’ll Be Doing

• Work with large and complex datasets to solve challenging business problems.
• Design, develop, train, and optimise machine learning models using modern algorithms and frameworks.
• Build and maintain production-grade, end-to-end ML pipelines covering data ingestion, transformation, training, validation, and deployment.
• Train and deploy standard ML, neural network, and agentic models efficiently.
• Automate model training, testing, and deployment through CI/CD pipelines and MLOps practices.
• Fine-tune SLMs and LLMs and develop complex AI architectures.
• Develop solutions across areas such as supervised and unsupervised learning, deep learning, NLP, computer vision, and generative AI.
• Collaborate with engineering, product, data, and other cross-functional teams to integrate AI models into applications and deliver end-to-end solutions.
• Design scalable ML system architectures and optimise models for real-time and batch inference.

What We’re Looking For

• 3-7 years’ experience building production-grade, scalable AI/ML systems.
• Strong expertise in machine learning, with experience across areas such as deep learning, NLP, computer vision, or generative AI/LLMs.
• Strong understanding of ML system architecture and productionisation.
• Experience with model serving and API development using tools such as FastAPI or Flask.
• Good understanding of Docker, Kubernetes, CI/CD, and MLOps tools such as MLflow or Kubeflow.
• Experience deploying machine learning models on AWS or Azure.
• Strong understanding of model performance optimisation and inference.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice to Have

• Master’s or PhD in Computer Science, Engineering, AI, or a related discipline.
• Hands-on experience with agentic AI systems and advanced LLM architectures.
• Experience designing and operating large-scale AI platforms in production.

The Opportunity

This is a great opportunity for an experienced Machine Learning Engineer to work on production-scale AI systems, from model development and experimentation through to deployment, automation, and continuous optimisation.