Machine Learning Engineer
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Key skills for this role
About the Role
A part-time, hybrid Machine Learning Engineer role in Abu Dhabi to design, develop, and maintain models for exam preparation content. Requires strong foundation in CS, algorithms, statistics, neural networks, and hands-on experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn.
Key Skills for This Role
Responsibilities
- Design, develop, and maintain models that personalize exam preparation content and recommend relevant learning resources
- Collect and preprocess data
- Experiment with algorithms and neural network architectures
- Implement pattern recognition techniques to improve user experience
- Evaluate model performance and optimize systems for accuracy and efficiency
- Collaborate with content and product teams to integrate ML solutions into the platform
- Document models, pipelines, and experimental results
- Support ongoing improvements to analytics and recommendation features
Requirements
- Strong foundation in Computer Science and Algorithms
- Proficiency in Statistics and Pattern Recognition
- Hands on experience with Neural Networks and modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn)
- Practical skills in data preprocessing, feature engineering, and model evaluation
- Bachelor’s degree or higher in Computer Science, Data Science, Engineering, or related quantitative field
- Experience with Python or similar programming languages, and familiarity with version control tools such as Git
- Ability to work collaboratively in a hybrid environment and communicate technical concepts clearly
- Experience with recommendation systems, educational technology, or exam preparation platforms is an advantage
Full Job Posting
Role Description
- This is a part time, hybrid Machine Learning Engineer role based in Abu Dhabi, with flexibility for some work from home.
- The Machine Learning Engineer will design, develop, and maintain models that personalize exam preparation content and recommend relevant learning resources.
- Daily tasks include collecting and preprocessing data, experimenting with algorithms and neural network architectures, and implementing pattern recognition techniques to improve user experience.
- The role also involves evaluating model performance, optimizing systems for accuracy and efficiency, and collaborating with content and product teams to integrate ML solutions into the platform.
- The engineer will document models, pipelines, and experimental results, and support ongoing improvements to analytics and recommendation features.
Qualifications
- Strong foundation in Computer Science and Algorithms, with experience implementing efficient and scalable solutions.
- Proficiency in Statistics and Pattern Recognition to analyze user behavior and model performance.
- Hands on experience with Neural Networks and modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn).
- Practical skills in data preprocessing, feature engineering, and model evaluation using appropriate metrics.
- Bachelor’s degree or higher in Computer Science, Data Science, Engineering, or a related quantitative field.
- Experience with Python or similar programming languages, and familiarity with version control tools such as Git.
- Ability to work collaboratively in a hybrid environment, communicate technical concepts clearly, and manage part time responsibilities effectively.
- Experience with recommendation systems, educational technology, or exam preparation platforms is an advantage.
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