Senior Machine Learning Engineer

Discovered MENA • Mena
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AI Summary

Lead the design, development, and deployment of scalable ML systems and pipelines. Build production-ready models, optimize performance using GPU acceleration, and drive best practices across the full ML lifecycle. Mentor engineers and work closely with stakeholders to deliver impactful AI solutions at scale.

Key Highlights
Relocation to Muscat, Oman required
Fast-growing technology organisation at the forefront of AI and machine learning innovation
Building scalable, production-grade machine learning systems
Key Responsibilities
Lead the design, development, and deployment of scalable ML systems and pipelines
Build production-ready models, optimize performance using GPU acceleration
Drive best practices across the full ML lifecycle
Mentor engineers and work closely with stakeholders to deliver impactful AI solutions at scale
Technical Skills Required
Python PyTorch TensorFlow MLOps MLflow Kubeflow CUDA TensorRT Cloud platforms Containerisation
Benefits & Perks
Relocation to Muscat, Oman
Relocation package provided

Job Description


Note* This role requires relocation to Muscat, Oman.


Our client is a fast-growing technology organisation at the forefront of AI and machine learning innovation, delivering advanced data-driven solutions across complex, high-impact environments. Operating at the intersection of software engineering, artificial intelligence, and high-performance computing, they are building scalable, production-grade machine learning systems that power critical business decisions and intelligent automation. With a strong focus on performance optimisation, cloud deployment, and real-world application of AI, the business is investing heavily in building a world-class engineering capability in the region.


They are now looking to hire a Senior Machine Learning Engineer to lead the design, development, and deployment of scalable ML systems and pipelines. This is a highly technical, hands-on role focused on building production-ready models, optimising performance using GPU acceleration (CUDA, TensorRT), and driving best practices across the full ML lifecycle. The role requires strong experience across Python, PyTorch/TensorFlow, MLOps (MLflow/Kubeflow), cloud platforms, and containerisation, alongside the ability to mentor engineers and work closely with stakeholders to deliver impactful AI solutions at scale.


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