🔹 1. AI Model DevelopmentDesign and build machine learning (ML) and deep learning (DL) models Work with frameworks like TensorFlow, PyTorch, Scikit-learn Train, test, and optimize models for accuracy and performance 🔹 2. Data Handling & PreprocessingCollect and clean structured/unstructured data Perform data preprocessing and feature engineering Work with large datasets using SQL, Python, or big data tools 🔹 3. Algorithm ImplementationDevelop AI algorithms such as: Natural Language Processing (NLP) Computer Vision Recommendation Systems Improve model efficiency and scalability 🔹 4. Model Deployment & IntegrationDeploy AI models into production environments Integrate AI solutions with web or mobile applications Use cloud platforms (AWS, Azure, Google Cloud) 🔹 5. Performance MonitoringMonitor model accuracy and performance Update and retrain models when required Fix bugs and improve system reliability 🔹 6. Collaboration & CommunicationWork with software developers, data scientists, and business teams Explain AI concepts to non-technical stakeholders Document AI solutions and workflows 🔹 7. Research & InnovationStay updated with latest AI trends Experiment with new tools and technologies Improve existing AI systems 🛠 Required SkillsTechnical Skills:Programming: Python, R, Java ML/DL Frameworks Data structures & algorithms Statistics & Mathematics Cloud & DevOps knowledge Soft Skills:Problem-solving Critical thinking Communication skills Team collaboration