Senior ML Engineer

NTG; Muscat; On-site; OMR 30,000 - 50,000; Full time

Job summary

NTG is hiring a Senior ML Engineer to develop the machine learning platform that supports national AI capabilities in Muscat. This role involves building and operating MLOps pipelines, ensuring models run efficiently at scale on a sovereign GPU fleet.

The ideal candidate has extensive experience in ML systems, is proficient in Python, and has a solid understanding of the MLOps lifecycle. A Bachelor's degree in Computer Science or a related field is required, and familiarity with Kubernetes is a plus.

Qualifications

• Experience in building and operating ML systems at scale.
• Strong foundation in MLOps including pipelines and model lifecycle.
• Proficient in Python and using modern ML stacks.

Responsibilities

• Build and operate the MLOps platform for model deployment.
• Take models from Data Scientists to scalable production.
• Monitor models in production and automate retraining.

Skills

MLOps

Machine Learning systems

Python

Kubernetes

GPU optimization

Education

Bachelor's degree in Computer Science or related field

Job description

Build the platform that trains, ships, and runs models at national scale, owning MLOps, pipelines, and efficient inference on a sovereign GPU fleet.

RQMNA builds the sovereign AI platforms that turn a nation's data into models running in production.

We are hiring a Senior ML Engineer, on site in Muscat, to build and run the machine learning platform behind a national AI capability.

Key Responsibilities

• Build and operate the MLOps platform: training pipelines, model registry, deployment, and serving
• Take models from the Data Scientist and research teams to reliable, scalable production
• Engineer model serving and inference, and optimize it for throughput, latency, and GPU efficiency
• Fine tune and train models at scale on a sovereign, on prem GPU fleet
• Build feature pipelines and a feature store, and automate the path from data to model to endpoint
• Monitor models in production: performance, drift, and automated retraining and rollback
• Bake reproducibility, versioning, and lineage into the model lifecycle
• Partner with the AI Engineer on serving GenAI and the Data Scientist on models, and set MLOps standards

What makes you a fit

• You have built ML systems and put models into production at scale, end to end
• You are strong in MLOps: pipelines, serving, monitoring, and the full model lifecycle
• You can train and fine tune models, and optimize inference on real GPU hardware
• You care about reproducibility, throughput, efficiency, and drift, not just accuracy
• You are fluent in Python and the modern ML and MLOps stack, and comfortable on Kubernetes
• You hold a Bachelor's or higher in Computer Science, Machine Learning, or a related field; an advanced degree is a plus
• You build platforms other engineers and scientists can rely on
• Bonus points for large scale training, GPU optimization, or sovereign and on prem ML
• Fluent English required; Arabic is a valuable advantage