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AI/ML Specialists (Data Scientists/ ML Engineer) at VAM Systems

Manama, Capital, Bahrain -

Full Time

Start Date

Immediate

Expiry Date

24 Jun, 26

Salary

0.0

Posted On

26 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, MLOps, Gen AI, RAG, Python, Supervised Learning, Unsupervised Learning, Model Evaluation, Feature Engineering, Azure ML, AWS SageMaker, Explainable AI, Data Preprocessing, AI Governance, Security Measures

Industry

IT Services and IT Consulting

Description

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)

Responsibilities

The role involves building and deploying Machine Learning models using Python and relevant libraries, focusing on AI use cases within the financial services industry. Specialists must ensure robust architecture, proper governance, and security measures for Generative AI solutions like chatbots and document analysis.