What Jobs are available for AI Intern in Bahrain?

• Assist in the collection, cleaning, and preprocessing of large datasets.
• Develop, train, and evaluate machine learning and deep learning models.
• Conduct research on emerging AI techniques and their potential applications.
• Write clean, efficient, and well-documented code in Python or R.
• Collaborate with the data science team on project design and implementation.
• Visualize data and model results for clear communication.
• Contribute to the documentation of models and methodologies.
• Participate in team discussions, code reviews, and knowledge sharing sessions.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• Solid understanding of machine learning algorithms and statistical modeling.
• Proficiency in Python and relevant data science libraries (e.g., pandas, NumPy, scikit-learn).
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to work independently and manage tasks effectively in a remote setting.
• Enthusiasm for AI and a strong desire to learn.

Minimum 5 years training experience in the selected training fieldAdequately Qualified with certificationsAble to train morning, afternoon & evening on training days Fluent in Arabic & English (Bilingual)

Job Type: Part-time

Expected hours: 20 per week

• Design, develop, and implement machine learning models and algorithms.
• Collect, clean, and preprocess large datasets for model training.
• Evaluate and optimize model performance using appropriate metrics.
• Deploy ML models into production environments and monitor their performance.
• Collaborate with data scientists and software engineers to integrate ML solutions.
• Stay updated with the latest research and advancements in machine learning.
• Develop and maintain documentation for ML models and systems.
• Contribute to the company's AI strategy and roadmap.

• Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related quantitative field.
• 3+ years of experience in machine learning engineering or a related role.
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of statistical modeling, algorithms, and data structures.
• Experience with data processing and database technologies.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.

• Design, develop, and implement machine learning models and algorithms.
• Process, clean, and analyze large datasets to extract valuable insights.
• Build and train deep learning models for various applications (e.g., NLP, computer vision).
• Deploy ML models into production environments, ensuring scalability and performance.
• Collaborate with data scientists, software engineers, and product managers to define project requirements.
• Stay abreast of the latest advancements in AI and machine learning research.
• Conduct experiments and A/B testing to evaluate model performance.
• Develop tools and frameworks to support the ML development lifecycle.
• Optimize ML pipelines for efficiency and accuracy.
• Document model architecture, development processes, and findings.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 3+ years of hands-on experience in developing and deploying machine learning models.
• Proficiency in programming languages such as Python and expertise in ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of statistical modeling, data mining, and algorithm development.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP) is a plus.
• Excellent problem-solving skills and analytical thinking.
• Strong communication and collaboration skills, with the ability to explain complex technical concepts.
• Ability to work independently and thrive in a remote, fast-paced environment.

• Design, develop, and implement machine learning models and algorithms for complex problems.
• Build and optimize scalable AI systems and pipelines for data processing, model training, and deployment.
• Perform data analysis, feature engineering, and model evaluation to ensure optimal performance.
• Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to integrate AI solutions into products and services.
• Stay current with the latest advancements in AI, machine learning, and deep learning research and apply them to practical challenges.
• Develop and maintain robust code for AI/ML models using Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Conduct experiments and rigorously test models to validate their effectiveness and identify areas for improvement.
• Document algorithms, models, and processes comprehensively.
• Troubleshoot and resolve issues related to AI model performance and deployment.
• Contribute to the intellectual property of the company through research and innovation.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Proven experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python, with extensive experience using libraries like TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, and Pandas.
• Solid understanding of various machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP) is highly desirable.
• Proficiency in data manipulation, statistical analysis, and data visualization techniques.
• Excellent problem-solving skills and the ability to tackle complex analytical challenges.
• Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders.
• Experience with MLOps practices is a significant plus.

• Design, develop, and implement machine learning models and algorithms for various applications, including predictive analytics, natural language processing, computer vision, and anomaly detection.
• Process, clean, and transform large datasets to prepare them for model training and evaluation.
• Collaborate with data scientists, software engineers, and domain experts to understand business requirements and translate them into technical solutions.
• Build and maintain robust data pipelines for model training, deployment, and monitoring.
• Evaluate model performance, identify areas for improvement, and implement optimizations.
• Stay abreast of the latest research and advancements in AI and machine learning, exploring new techniques and tools.
• Develop and deploy AI models into production environments, ensuring scalability and efficiency.
• Conduct experiments and A/B testing to validate model performance and impact.
• Document technical specifications, model designs, and research findings thoroughly.
• Contribute to the development of AI strategy and roadmap.
• Troubleshoot and resolve issues related to AI models and systems.
• Collaborate on building and enhancing AI platforms and infrastructure.
• Mentor junior team members and share knowledge on AI/ML best practices.
• Ensure ethical considerations and bias mitigation are addressed in AI development.
• Present findings and insights to technical and non-technical stakeholders.

• Design, develop, and implement advanced machine learning models and algorithms.
• Process, clean, and analyze large-scale datasets to extract actionable insights.
• Build and deploy AI-powered solutions for various applications.
• Evaluate model performance, identify areas for improvement, and iterate on solutions.
• Stay abreast of the latest research and advancements in AI and machine learning.
• Collaborate with software engineers and data scientists to integrate ML models into production systems.
• Develop and maintain robust MLOps pipelines for model training, deployment, and monitoring.
• Contribute to the overall AI strategy and roadmap of the company.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Participate in code reviews and contribute to a high standard of code quality.
• Work effectively in a fully remote, asynchronous and synchronous collaboration environment.
• Mentor junior team members and share knowledge.
• Research and experiment with new AI technologies and frameworks.

• Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
• Proven experience in developing and deploying machine learning models in production.
• Strong proficiency in programming languages such as Python, R, or Scala.
• Expertise in ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Solid understanding of statistical modeling, data mining, and machine learning algorithms.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (Spark, Hadoop).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills for remote teamwork.
• Ability to work independently and manage time effectively in a remote setting.
• Experience with MLOps practices and tools is a plus.

• Design, develop, and implement advanced machine learning models, including deep learning, reinforcement learning, and natural language processing.
• Build and maintain robust data pipelines for model training and deployment.
• Conduct exploratory data analysis to identify patterns, insights, and opportunities for AI-driven solutions.
• Evaluate and compare different ML algorithms and frameworks to select the most appropriate solutions for specific problems.
• Optimize model performance for accuracy, scalability, and efficiency.
• Collaborate closely with software engineers and product managers to integrate AI/ML capabilities into existing and new products.
• Stay current with the latest research and advancements in AI, ML, and related fields.
• Develop and implement MLOps practices for continuous integration, deployment, and monitoring of ML models.
• Present complex technical concepts and findings to both technical and non-technical stakeholders.
• Contribute to the team's knowledge base through documentation, code reviews, and knowledge sharing sessions.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.
• Proven experience (5+ years) in developing and deploying production-level machine learning models.
• Strong programming skills in Python and proficiency with ML libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
• Solid understanding of algorithms, data structures, and statistical modeling.
• Experience with cloud platforms like AWS, Azure, or GCP and their ML services.
• Familiarity with big data technologies (e.g., Spark, Hadoop) and database management.
• Excellent problem-solving abilities and a strong analytical mindset.
• Effective communication and collaboration skills, adept at working within a remote team structure.
• Experience with MLOps tools and methodologies (e.g., Docker, Kubernetes, MLflow) is a significant plus.
• A passion for innovation and a proactive approach to tackling challenging technical problems.

• Lead the design, development, and implementation of advanced AI and machine learning models.
• Define the AI roadmap and strategy in alignment with business objectives.
• Manage and mentor a team of data scientists and ML engineers, fostering a collaborative and innovative environment.
• Oversee the end-to-end machine learning lifecycle, from data collection and preprocessing to model training, evaluation, and deployment.
• Identify new opportunities for leveraging AI and ML to solve complex business problems.
• Stay abreast of the latest research and developments in AI and machine learning.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and products.
• Ensure the ethical and responsible use of AI technologies.
• Evaluate and implement appropriate tools and technologies for AI development and deployment.
• Present findings and recommendations to senior leadership.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
• Minimum of 7 years of experience in AI/ML research and development, with a proven track record of delivering impactful solutions.
• Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Proficiency in programming languages such as Python or R.
• Strong understanding of various ML algorithms, deep learning architectures, and data mining techniques.
• Experience leading technical teams and managing projects.
• Excellent communication, presentation, and interpersonal skills.
• Ability to translate complex technical concepts into business value.