Machine Learning Engineer
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Key skills for this role
About the Role
Network. Lead. Exchange.
Key Skills for This Role
Responsibilities
- Design, develop, and optimize machine learning models to support data driven insights
- Collect and preprocess data
- Implement and train algorithms and neural network architectures
- Evaluate model performance and prepare clear reports or dashboards for stakeholders
- Collaborate with business and technical teams to translate networking and community needs into practical ML solutions
- Maintain code quality and documentation
- Stay current with emerging tools and techniques in machine learning
Requirements
- Strong background in Computer Science and Algorithms
- Proficiency in Pattern Recognition and Neural Networks
- Solid understanding of Statistics for model evaluation, hypothesis testing, and data analysis
- Experience with common ML tools and languages (e.g., Python, TensorFlow, PyTorch, scikit learn) and version control systems
- Bachelor’s degree or higher in Computer Science, Data Science, Engineering, or a related quantitative field
- Ability to communicate technical concepts clearly to non technical stakeholders
Full Job Posting
Role Description
- This is a part time hybrid role for a Machine Learning Engineer based in Abu Dhabi, with flexibility for some work from home. The Machine Learning Engineer will design, develop, and optimize machine learning models to support data driven insights for the organization and its members.
Day to day tasks
- Collecting and preprocessing data, implementing and training algorithms and neural network architectures, evaluating model performance, and preparing clear reports or dashboards for stakeholders.
- Collaborating with business and technical teams to translate networking and community needs into practical ML solutions, maintaining code quality and documentation, and staying current with emerging tools and techniques in machine learning.
Qualifications
- Strong background in Computer Science and Algorithms, with the ability to design efficient and scalable solutions.
- Proficiency in Pattern Recognition and Neural Networks for building predictive and classification models.
- Solid understanding of Statistics for model evaluation, hypothesis testing, and data analysis.
- Experience with common ML tools and languages (e.g., Python, TensorFlow, PyTorch, scikit learn) and version control systems.
- Bachelor’s degree or higher in Computer Science, Data Science, Engineering, or a related quantitative field.
- Ability to communicate technical concepts clearly to non technical stakeholders and work collaboratively in a diverse team environment.
- Experience with data pipelines, cloud platforms, or MLOps practices is an advantage.
- Interest in business networking, entrepreneurship, or community driven initiatives is beneficial.
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