569 Learning jobs in Bahrain
Curriculum Development Specialist - Online Learning
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Qualifications:
- Master's degree in Education, Instructional Design, or a related field.
- Minimum of 5 years of experience in curriculum development and instructional design, with a focus on online learning.
- Demonstrated expertise in learning theories and pedagogical approaches for online environments.
- Proficiency with learning management systems (e.g., Moodle, Canvas, Blackboard).
- Experience with multimedia content creation tools (e.g., Articulate Storyline, Adobe Captivate).
- Excellent writing, editing, and communication skills.
- Strong project management and organizational abilities.
Curriculum Development Specialist - Online Learning
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Curriculum Development Specialist - Online Learning
Posted today
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Machine Learning Engineer
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Responsibilities:
- Develop, train, and deploy machine learning models using various algorithms and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Build and maintain scalable machine learning pipelines for data processing, feature engineering, and model evaluation.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Monitor model performance in production and implement strategies for continuous improvement and retraining.
- Perform data analysis and feature engineering to enhance model accuracy.
- Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
- Design and implement experiments to test hypotheses and evaluate model performance.
- Ensure the responsible and ethical use of AI and machine learning technologies.
- Optimize ML models for performance, scalability, and efficiency.
- Communicate complex technical concepts to both technical and non-technical stakeholders.
- Troubleshoot and resolve issues related to ML model deployment and performance.
- Contribute to the documentation of ML models, pipelines, and processes.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
- Minimum of 4 years of experience in machine learning engineering or a related role.
- Strong programming skills in Python and experience with ML libraries.
- Proven experience in building and deploying machine learning models in production.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Solid understanding of data structures, algorithms, and software engineering principles.
- Experience with SQL and NoSQL databases.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and collaboration skills.
- Ability to work effectively in a hybrid work environment.
Online Learning Specialist
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Key Responsibilities:
- Provide technical and instructional support to online instructors and students using the Learning Management System (LMS) and other online learning tools.
- Assist instructors in uploading course materials, creating assignments, and setting up online assessments.
- Monitor online course activities, ensuring smooth operation and addressing any technical issues promptly.
- Facilitate communication between students and instructors, fostering an engaged learning community.
- Develop and maintain user guides, tutorials, and FAQs for online learning platforms and tools.
- Assist in the creation and management of online course content, ensuring adherence to quality standards.
- Support the administration of online assessments and grade management.
- Analyze user feedback and course data to identify areas for improvement in the online learning experience.
- Collaborate with the instructional design team on new course development and existing course revisions.
- Stay updated on best practices in online education and learning technologies.
- Manage user accounts and access permissions within the LMS.
- Troubleshoot and resolve technical problems encountered by users in the online learning environment.
- Bachelor's degree in Education, Information Technology, or a related field.
- Minimum of 2-4 years of experience in an online learning support, educational technology, or similar role.
- Proficiency with Learning Management Systems (LMS) such as Moodle, Canvas, Blackboard, or similar platforms.
- Strong understanding of online pedagogy and instructional design principles.
- Excellent technical troubleshooting and problem-solving skills.
- Exceptional communication, interpersonal, and customer service skills.
- Ability to work independently and manage tasks effectively in a remote setting.
- Detail-oriented with strong organizational and time management abilities.
- Experience with multimedia content creation tools is a plus.
- Knowledge of various educational technologies and platforms.
Machine Learning Engineer
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Key Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Preprocess, clean, and engineer features from large, complex datasets.
- Train, evaluate, and optimize ML models for performance and accuracy.
- Deploy ML models into production environments using MLOps practices.
- Collaborate with data scientists and engineers to integrate ML solutions.
- Research and apply the latest AI and ML techniques and technologies.
- Develop and maintain documentation for ML models and pipelines.
- Monitor model performance in production and retrain as needed.
- Contribute to the development of AI strategy and roadmap.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- 3+ years of experience in machine learning engineering or data science with a focus on applied ML.
- Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
- Solid understanding of statistical modeling, data mining, and machine learning algorithms.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
Machine Learning Engineer
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Responsibilities:
- Design, develop, and implement machine learning models and algorithms.
- Perform data preprocessing, feature engineering, and data analysis to prepare datasets for model training.
- Train, evaluate, and optimize machine learning models for performance and accuracy.
- Deploy machine learning models into production environments.
- Collaborate with data scientists and software engineers to integrate ML solutions into existing systems.
- Stay current with the latest advancements in AI and machine learning research and techniques.
- Develop and maintain robust MLOps pipelines for model deployment and monitoring.
- Conduct experiments and research to explore new ML approaches.
- Write clean, efficient, and well-documented code.
- Communicate technical findings and model performance to stakeholders.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 4-6 years of experience in machine learning engineering or data science.
- Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of statistical modeling, algorithms, and machine learning concepts.
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Proven experience in data preprocessing, feature engineering, and model evaluation.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Experience with big data technologies (e.g., Spark) is a plus.
- Published research in reputable ML conferences or journals is a plus.
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Machine Learning Engineer
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Key Responsibilities:
- Design, develop, train, and deploy machine learning models and algorithms.
- Implement and manage data pipelines for model training and evaluation.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Optimize model performance for accuracy, scalability, and efficiency.
- Stay up-to-date with the latest advancements in machine learning, deep learning, and AI research.
- Develop robust testing and validation strategies for ML models.
- Monitor deployed models for performance drift and implement retraining strategies.
- Work with large datasets, performing feature engineering and selection.
- Contribute to the architectural design of ML platforms and infrastructure.
- Document model development processes, findings, and deployment procedures.
Qualifications:
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 5 years of experience in machine learning engineering or data science with a focus on model development and deployment.
- Proficiency in programming languages such as Python (with libraries like TensorFlow, PyTorch, Scikit-learn, Pandas).
- Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Solid understanding of various ML algorithms, including supervised, unsupervised, and deep learning techniques.
- Experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow).
- Strong analytical, problem-solving, and critical thinking skills.
- Excellent communication and collaboration abilities.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Ability to work effectively in a fast-paced, dynamic environment.
This position offers a highly competitive salary, comprehensive benefits package, and the opportunity to work on groundbreaking AI projects.
Machine Learning Engineer
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Key responsibilities include developing robust and scalable machine learning pipelines, from data preprocessing and feature engineering to model evaluation and deployment. You will collaborate with data scientists and software engineers to implement and optimize ML algorithms. Ensuring the performance, accuracy, and reliability of deployed models will be a core duty. You will also be responsible for monitoring model performance in production, identifying drift, and implementing retraining strategies. Contributing to the design and development of ML infrastructure and tooling is expected. Staying current with state-of-the-art ML techniques and contributing to the team's knowledge base are essential. You will also participate in code reviews and contribute to documentation.
The ideal candidate will hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field. Proven experience in building and deploying machine learning models in a production environment is required. Proficiency in programming languages such as Python, and experience with ML libraries and frameworks like Scikit-learn, TensorFlow, or PyTorch, are mandatory. Strong understanding of data structures, algorithms, and software engineering best practices is essential. Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) is highly desirable. Excellent analytical, problem-solving, and communication skills are crucial. Join our innovative team and help us build the next generation of AI-powered products.
Senior Machine Learning Engineer
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