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AI/ML Specialists (Data Scientists/ ML Engineer)

VAMSystems

Manama, , Bahrain permanent

Posted: March 8, 2026

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Quick Summary

We are looking for an experienced AI/ML Specialist/Dat Scientist/ML Engineer with a strong background in computer science/engineering and experience with machine learning, deep learning, and MLOps. The ideal candidate should have 7-10 years of experience and be proficient in Google Professional ML Engineer and Microsoft AI Engineer Associate Professional Licenses. The ideal candidate should also have expertise in AI in financial services.

Job Description

VAM Systems is currently looking for AI/ML Specialists (Data Scientists/ ML Engineer) (On-Site) for our Bahrain operations with the following skillsets and terms & conditions:

Years of Experience: 7 – 10 years

Qualification

Bachelor’s Degree in Computer Science / Engineering

Preferably BE Computer Science & Engineering

Professional Training Required: Machine Learning, Deep Learning, MLOps, AI in Financial Services.

Professional Qualification Required: Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable.

Professional Certifications Required: TensorFlow Developer Certificate, AWS Certified Machine Learning.

Must-Have:

•Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures

•Several years of ML experience with implemented use cases.

•Hands-on work experience most of which in banking, financial institutions, or insurance industries.

Experience required:

Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms.

Experience with model evaluation and performance metrics.

Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering.

Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management.

Ability to communicate insights and build explainable AI models.

Joining time frame: (15 - 30 days)

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