Senior AI/ML Engineer
Summary
Senior AI/ML Engineer in Manama, Bahrain who designs, builds, and deploys machine-learning solutions for product and operational needs. Day-to-day work spans data preparation, model training and evaluation, and production integration via APIs, containers, or cloud, using Python with libraries like NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
Job Description
The 4 Point Management is a software technology development engineering company seeking a Senior AI/ML Engineer for its team in Manama, Bahrain. In this full-time role, you will design and deliver machine-learning solutions that address product and operational needs, working closely with software engineering and relevant business stakeholders.
Responsibilities include:
- Develop, train, evaluate, and improve machine-learning models using suitable algorithms and data.
- Prepare and analyze datasets, identify quality issues, and build reliable data-processing workflows.
- Translate product requirements into AI/ML approaches, prototypes, and production-ready services.
- Integrate models into software applications and support deployment, monitoring, and ongoing performance optimization.
- Establish sound practices for experimentation, reproducibility, testing, documentation, and model lifecycle management.
- Collaborate with engineers and stakeholders to communicate findings, estimate work, and deliver dependable solutions.
The position is based in Manama and is not designated as a remote role. The successful candidate will contribute hands-on technical expertise while helping advance the company’s software development capabilities.
Job Specification
- Strong applied machine-learning knowledge, including supervised and unsupervised learning, model selection, validation, and performance tuning.
- Proficiency in Python and common data and ML libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
- Experience preparing datasets, feature engineering, exploratory analysis, and building repeatable data-processing pipelines.
- Ability to deploy and integrate models into production software using APIs, containers, or cloud-based services.
- Working knowledge of model monitoring, testing, version control, experiment tracking, and reproducible development practices.
- Strong software engineering fundamentals, including readable code, debugging, documentation, and collaborative code review.
- Analytical problem-solving skills and the ability to explain technical trade-offs and results to cross-functional stakeholders.