Question
Full-time
5-10

AI/ML Specialists (Data Scientists/ ML Engineer) - Banking

1/4/2026

The AI/ML Specialist will be responsible for delivering Gen AI solutions in banking and financial institutions, focusing on areas such as chatbots and document analysis. They will leverage robust architecture with proper governance and security measures.

Working Hours

40 hours/week

Company Size

51-200 employees

Language

English

Visa Sponsorship

No

About The Company
VAM Systems is a Business Consulting, Technology Solutions and Professional Services organization working with major organizations in USA, UAE, Bahrain, India, Singapore and Australia. Delivers leading edge information and communication technology based business solutions to enable our clients to continuously stay ahead and achieve sustainable profit and consistent growth by leveraging new channels of customer engagement and service delivery as well as better and efficient employment of resources and processes with measurable parameters for performance. While our local presence assists us in better understanding of the local needs, our global presence assist us to offer solutions strengthened by experience in leading markets globally.
About the Role

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)

Key Skills
Machine LearningDeep LearningMLOpsAI in Financial ServicesPythonSupervised LearningUnsupervised LearningModel EvaluationPerformance MetricsData PreprocessingFeature EngineeringCloud-Based ML PlatformsAzure MLAWS SageMakerExplainable AIGen AI Solutions
Categories
TechnologyData & AnalyticsFinance & Accounting
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