Senior Machine Learning Engineer (MLOps)

About the role

RQMNA is building a sovereign AI platform that turns national data into production‑ready models. We are looking for a Senior Machine Learning Engineer to design, implement, and operate the end‑to‑end MLOps platform that powers this capability, working on‑site in Muscat.

Key responsibilities

• Design, build, and run the MLOps platform, including training pipelines, model registry, deployment, and serving.
• Take models from data‑science and research teams to reliable, scalable production.
• Engineer model serving and inference, optimizing throughput, latency, and GPU efficiency.
• Fine‑tune and train large models on an on‑prem sovereign GPU fleet.
• Create feature pipelines and a feature store, automating the path from data to model to endpoint.
• Monitor production models for performance, drift, and manage automated retraining and rollback.
• Integrate reproducibility, versioning, and lineage throughout the model lifecycle.
• Collaborate with AI Engineers on GenAI serving and set MLOps standards across teams.

Required profile

• Proven experience building ML systems and delivering models to production at scale.
• Deep expertise in MLOps, including pipelines, serving, monitoring, and full lifecycle management.
• Hands‑on ability to train, fine‑tune, and optimise inference on GPU hardware.
• Strong focus on reproducibility, efficiency, and handling model drift.
• Fluent in Python and comfortable with modern MLOps tooling and Kubernetes.
• Bachelor’s degree in Computer Science, Machine Learning, or related field; advanced degree is a plus.

Required skills

• Python
• Kubernetes
• GPU hardware optimisation
• MLOps tooling (training pipelines, model registry, deployment, monitoring)