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AI/ML Specialists Banking
Job summary
A leading technology firm is looking for AI/ML Specialists (Data Scientists/ML Engineers) with 7 to 10 years of experience. You will focus on delivering solutions in banking, leveraging your expertise in machine learning, deep learning, and MLOps. The ideal candidate should have a Bachelor's degree in Computer Science, proven experience in Gen AI solutions, and skills in Python and relevant libraries. The role is on-site, with a joining time frame of 15 to 30 days.
Qualifications
- 7 - 10 years of experience in AI/ML roles, preferably in banking or finance.
- Proven delivery experience in Gen AI solutions like chatbots.
- Hands-on experience with ML model deployment and life cycle.
Responsibilities
- Build and deploy ML models using Python and libraries.
- Understand supervised and unsupervised learning algorithms.
- Work with cloud-based ML platforms and manage model lifecycle.
Skills
Education
Tools
- Full-time
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
Bachelor’s Degree in Computer Science / Engineering
Preferably BE Computer Science & Engineering
- Machine Learning
- Deep Learning
- MLOps
- AI in Financial Services
- Google Professional ML Engineer
- Microsoft AI Engineer Associate Professional Licenses Required Not applicable
- TensorFlow Developer Certificate
- AWS Certified Machine Learning
- 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.
- 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)
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.