802 Machine Learning Manager jobs in Bahrain

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

• Developing and implementing machine learning algorithms and models using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Processing and analyzing large datasets to extract meaningful features and insights.
• Designing, training, and evaluating machine learning models for various applications.
• Deploying machine learning models into production environments.
• Collaborating with software engineers to integrate ML models into existing systems and applications.
• Conducting research on new AI and ML techniques and exploring their potential applications.
• Monitoring and maintaining deployed models, iterating as needed.
• Communicating complex technical concepts and results to both technical and non-technical stakeholders.
• Staying current with academic research and industry trends in machine learning and AI.

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience.
• Proven experience in building and deploying machine learning models.
• Strong programming skills in Python and expertise in ML libraries.
• Solid understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps principles.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work effectively in a hybrid work environment.

• Develop, train, and evaluate machine learning models using various algorithms and techniques.
• Implement and optimize ML pipelines for data preprocessing, feature engineering, model training, and deployment.
• Collaborate with data scientists to understand model requirements and performance metrics.
• Build and maintain scalable ML infrastructure and systems.
• Deploy ML models into production environments, ensuring their reliability and efficiency.
• Monitor model performance in production and implement necessary updates or retrainings.
• Work with large datasets, ensuring data quality and integrity for ML applications.
• Contribute to the design and architecture of AI-powered products and services.
• Stay current with the latest advancements in machine learning and artificial intelligence research.
• Write clean, well-documented, and maintainable code.
• Troubleshoot and resolve issues related to ML models and systems.
• Collaborate with software engineers to integrate ML models into existing applications.
• Present findings and results to technical and non-technical stakeholders.
• Contribute to the company's strategy for leveraging AI and machine learning.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• 2+ years of professional experience in machine learning engineering or a similar role.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Solid understanding of various ML algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with data processing and manipulation tools (e.g., Pandas, Spark).
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Knowledge of MLOps principles and practices is a plus.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork abilities.
• Ability to work effectively in a fast-paced, collaborative office environment.

• Design, build, and maintain scalable machine learning systems and infrastructure.
• Develop and implement machine learning models using state-of-the-art algorithms.
• Process and analyze large datasets to extract valuable insights.
• Perform feature engineering, model training, evaluation, and optimization.
• Deploy ML models into production environments and monitor their performance.
• Collaborate with data scientists and software engineers to integrate ML solutions.
• Stay current with the latest advancements in AI, machine learning, and deep learning.
• Conduct research and experiments to explore new ML techniques and applications.
• Document ML models, pipelines, and processes.
• Troubleshoot and resolve issues related to ML systems.

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 3-5 years of professional experience in machine learning engineering.
• Proficiency in programming languages like Python and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Strong understanding of algorithms, data structures, and software development principles.
• Excellent analytical, problem-solving, and communication skills.
• Experience in deploying ML models in production.
• Ability to work effectively in a hybrid team setting.

• Design, build, and maintain production-grade machine learning systems and pipelines.
• Develop and implement data processing, feature engineering, and model training strategies.
• Optimize ML models for performance, scalability, and efficiency.
• Deploy ML models into production environments using CI/CD and MLOps practices.
• Collaborate with data scientists to translate research models into deployable applications.
• Monitor and maintain deployed ML models, ensuring accuracy and reliability.
• Stay up-to-date with the latest advancements in ML research and technology.

• Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field.
• 3+ years of experience in machine learning engineering or a similar role.
• Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, XGBoost).
• Proficiency with deep learning frameworks (TensorFlow, PyTorch).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
• Solid understanding of software development best practices.
• Excellent problem-solving and analytical skills.

• Design, develop, and implement state-of-the-art machine learning models for various applications, including predictive analytics, natural language processing, computer vision, and recommendation systems.
• Clean, process, and analyze large, complex datasets to extract meaningful features and insights.
• Build and optimize scalable machine learning pipelines for training, validation, and deployment.
• Evaluate and select appropriate algorithms and frameworks based on project requirements and data characteristics.
• Collaborate closely with data scientists, software engineers, and domain experts to integrate ML models into production systems.
• Conduct rigorous testing and validation of models to ensure accuracy, robustness, and performance.
• Stay abreast of the latest research and advancements in machine learning, deep learning, and artificial intelligence.
• Develop and maintain high-quality, well-documented code and documentation for ML models and experiments.
• Mentor junior ML engineers and contribute to the team's knowledge sharing and best practices.
• Identify opportunities to leverage AI and ML to solve business problems and create new value.
• Monitor deployed models and implement strategies for continuous improvement and retraining.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
• 7+ years of experience in machine learning engineering or a related data science role.
• Deep understanding of fundamental ML concepts, algorithms (e.g., regression, classification, clustering, deep learning), and their applications.
• Proficiency in programming languages such as Python (with libraries like TensorFlow, PyTorch, scikit-learn, Keras) and/or R.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Strong data manipulation and analysis skills.
• Familiarity with MLOps principles and practices.
• Excellent analytical, problem-solving, and critical thinking abilities.
• Strong communication and collaboration skills, suitable for a remote work environment.
• Experience with natural language processing (NLP) or computer vision is a strong plus.