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AI/ML Engineer

AMOUAGE · Mascate

جديد
🇬🇧 English
Python scikit-learn PyTorch TensorFlow LLM RAG embeddings prompt engineering computer vision image classification object detection SQL REST APIs Azure AWS Google Cloud Git Docker CI/CD MLOps Kubernetes

وصف الوظيفة

About the role

Join the House of AMOUAGE’s Digital Transformation team in Muscat to design and deliver AI solutions that boost operational efficiency and enhance digital experiences across the luxury fragrance business.

Key responsibilities

  • Translate business needs into AI use cases, define success metrics and delivery priorities.
  • Develop, test, and deploy machine learning models, moving prototypes to production.
  • Build generative AI solutions using large language models, retrieval‑augmented generation and vector search.
  • Create computer‑vision applications for image classification, object detection and verification.
  • Prepare and validate data, engineer features, and evaluate models against baselines.
  • Integrate AI services with enterprise applications, databases and cloud platforms via secure APIs.
  • Implement MLOps practices for versioning, deployment, monitoring, drift detection and retraining.
  • Apply AI security, privacy and governance controls and document solutions for support and adoption.

Required profile

  • Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering or a related field.
  • Proven experience delivering AI/ML solutions in production with measurable business impact.
  • Strong analytical, communication and collaborative skills, with a commitment to continuous learning.

Required skills

  • Python programming and libraries such as scikit‑learn, PyTorch or TensorFlow.
  • Hands‑on experience with LLMs, embeddings, prompt engineering, RAG and model evaluation.
  • Computer‑vision expertise (image classification, object detection, verification).
  • SQL, data preparation, feature engineering and handling diverse datasets.
  • Developing REST APIs and integrating AI services with enterprise systems.
  • Familiarity with Azure, AWS or Google Cloud, Git, Docker and CI/CD pipelines.
  • Knowledge of MLOps, model monitoring, privacy, responsible AI; Kubernetes is a plus.

Questions fréquentes

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