What Jobs are available for AI Prompter in Bahrain?

• Conduct independent, high-impact research in Artificial Intelligence and related areas.
• Publish research findings in leading academic journals and present at international conferences.
• Develop and deliver engaging lectures and course materials for undergraduate and graduate students in AI, machine learning, deep learning, and related subjects.
• Supervise student research projects, theses, and dissertations.
• Mentor and advise students on academic and career paths.
• Contribute to curriculum development and departmental initiatives.
• Seek external funding to support research activities.
• Collaborate with faculty across different departments on interdisciplinary projects.
• Participate in faculty governance and committee work.
• Promote the university's commitment to academic excellence and innovation.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
• A strong record of scholarly publication in reputable journals and conferences.
• Demonstrated success in securing research grants and funding.
• Proven experience in teaching at the university level, with excellent pedagogical skills.
• Expertise in core AI concepts, including machine learning, deep learning, natural language processing, computer vision, or robotics.
• Ability to develop and teach a diverse range of AI courses.
• Excellent communication, presentation, and interpersonal skills.
• A commitment to fostering an inclusive and supportive learning environment.
• Experience in guiding student research is highly desirable.
• Postdoctoral research experience is a significant advantage.

• Lead and conduct cutting-edge research in AI/ML domains.
• Develop and implement novel algorithms and models.
• Design and execute experiments to validate research hypotheses.
• Publish research findings in top-tier academic conferences and journals.
• Collaborate with engineering teams to translate research into practical applications.
• Mentor and guide junior researchers and scientists.
• Stay abreast of the latest advancements and trends in AI research.
• Contribute to the strategic direction of the organization's AI initiatives.
• Present research findings and proposals to stakeholders and management.

• Ph.D. in Computer Science, AI, ML, Statistics, or a related quantitative field.
• 8+ years of post-doctoral research experience in AI/ML.
• Proven track record of significant research contributions (publications, patents).
• Deep expertise in areas such as deep learning, NLP, computer vision, etc.
• Strong programming skills in Python and deep learning frameworks.
• Experience with large-scale data and distributed computing is a plus.
• Excellent analytical, critical thinking, and communication skills.
• Ability to thrive in a hybrid work environment.

• Leading the design and execution of research projects on AI in education.
• Developing and testing AI models for personalized learning, intelligent tutoring systems, and educational analytics.
• Conducting rigorous empirical research, including qualitative and quantitative data analysis.
• Publishing research findings in leading academic journals and presenting at international conferences.
• Collaborating with cross-functional teams, including educators, software developers, and policymakers.
• Securing external funding through grant writing and proposals.
• Mentoring junior researchers and students.
• Contributing to the strategic direction of AI in education research initiatives.

• Ph.D. in Computer Science, Education Technology, Artificial Intelligence, or a related field.
• Minimum of 6 years of post-doctoral research experience in AI or educational technology.
• Demonstrated expertise in machine learning, natural language processing, or related AI fields.
• Experience with research methodologies relevant to education.
• Strong publication record in reputable venues.
• Proficiency in programming languages like Python.
• Excellent communication, collaboration, and project management skills.
• Experience working in a remote research environment.

Apt Resources is seeking an experienced Machine Learning Engineer for a client in Abu Dhabi's Government & Public Sector. In this role, you will design and deploy cutting-edge AI/ML solutions using Large Language Models (LLMs) like GPT, Llama, and BERT to drive innovation in public services.

This is an exciting opportunity to work on high-impact projects involving Retrieval-Augmented Generation (RAG), fine-tuning, and prompt engineering, ensuring secure, scalable, and compliant AI systems for government applications.

• Develop and optimize AI/ML pipelines for LLMs, focusing on RAG architectures, fine-tuning, and prompt engineering tailored for public sector needs.
• Implement scalable solutions using Python, LangChain, HuggingFace, PyTorch/TensorFlow, and cloud-based ML services (Azure ML preferred).
• Integrate vector/graph databases (Weaviate, Neo4j) into production systems to enhance data retrieval and analysis.
• Deploy and monitor models in production, ensuring adherence to government security and compliance standards.
• Collaborate with cross-functional teams to align AI solutions with public sector objectives (e.g., citizen services, data governance, operational efficiency).

• 6-14 years of hands-on experience in AI/ML, with a strong focus on LLMs and GenAI.
• Expertise in LLM architectures (Transformers), prompt engineering, and RAG implementations.
• Proficiency in Python and ML frameworks (LangChain, LlamaIndex, HuggingFace, Scikit-learn).
• Experience with cloud platforms (Azure ML, AWS, or GCP) and MLOps tools (MLflow, model monitoring).
• Familiarity with vector databases, ETL pipelines, and unstructured data handling.
• Knowledge of government IT standards or secure deployments is a plus.

To be discussed

• Design, develop, and implement machine learning models and algorithms.
• Preprocess, clean, and analyze large datasets for model training.
• Perform feature engineering and selection to enhance model performance.
• Train, evaluate, and optimize machine learning models.
• Deploy models into production environments and monitor their performance.
• Collaborate with data scientists and software engineers on AI initiatives.
• Research and stay current with the latest advancements in machine learning and AI.
• Develop and maintain ML pipelines and infrastructure.
• Troubleshoot and debug machine learning systems.
• Document model designs, methodologies, and results.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related field.
• 3-5 years of experience in machine learning engineering or a similar role.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Strong understanding of various machine learning algorithms (e.g., supervised, unsupervised, deep learning).
• Experience with cloud platforms (AWS, Azure, GCP) for ML development is desirable.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Experience in MLOps and model deployment is a significant advantage.
• Ability to work effectively in a hybrid work environment.

• Design, build, and maintain production-ready machine learning models and pipelines.
• Collaborate with data scientists to translate ML models into scalable software solutions.
• Develop and implement strategies for data preprocessing, feature engineering, and model training.
• Optimize ML algorithms for performance, efficiency, and scalability.
• Deploy ML models into production environments and monitor their performance over time.
• Work with software engineering teams to integrate ML capabilities into existing products and services.
• Develop automated testing and validation procedures for ML models.
• Stay current with the latest advancements in machine learning, deep learning, and MLOps.
• Troubleshoot and resolve issues related to model performance and data integrity.
• Contribute to the continuous improvement of our ML infrastructure and best practices.
• Document ML models, code, and deployment processes clearly.

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Minimum of 3 years of experience as a Machine Learning Engineer or in a similar role.
• Strong programming skills in Python and experience with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Proficiency in data manipulation and analysis tools (e.g., Pandas, SQL).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Familiarity with MLOps principles and tools for model deployment and monitoring.
• Solid understanding of machine learning algorithms and statistical modeling.
• Excellent problem-solving and analytical skills.
• Good communication skills and ability to work effectively in a team environment.
• Experience with big data technologies (e.g., Spark) is a plus.

• Develop, implement, and deploy machine learning models and algorithms for various applications.
• Design and build data pipelines for training, testing, and deploying ML models efficiently.
• Collaborate with data scientists and researchers to productionize research prototypes.
• Optimize ML models for performance, scalability, and efficiency in production environments.
• Implement and maintain MLOps practices, including model monitoring, versioning, and automated retraining.
• Work with large, complex datasets, ensuring data quality and integrity.
• Develop APIs and services to integrate ML models into existing applications and platforms.
• Evaluate and select appropriate ML frameworks, tools, and technologies.
• Troubleshoot and debug ML systems, identifying and resolving issues in production.
• Stay up-to-date with the latest advancements in machine learning and software engineering best practices.
• Document ML models, pipelines, and deployment processes.
• Contribute to the overall architecture and design of AI-powered solutions.
• Collaborate with software engineers to integrate ML components into larger systems.

• Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related quantitative field, or equivalent practical experience.
• Proven experience as a Machine Learning Engineer or in a similar role focused on deploying ML models.
• Strong programming skills in Python and proficiency with ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Keras).
• Experience with cloud platforms (AWS, Azure, GCP) and associated ML services.
• Solid understanding of software development best practices, including version control (Git), CI/CD, and testing.
• Experience with data processing frameworks (e.g., Spark, Dask) and database technologies.
• Knowledge of MLOps principles and tools is highly desirable.
• Excellent analytical and problem-solving skills.
• Strong communication and teamwork abilities.
• Ability to work effectively in a fast-paced, collaborative environment.