AI Developer

- AI Model Development: Design, develop, and deploy AI models, including machine learning and deep learning algorithms, for various applications such as natural language processing, computer vision, recommendation systems, and predictive analytics. - Data Preprocessing: Work with large-scale datasets, perform data cleaning, feature engineering, and data augmentation to prepare data for training AI models. - Model Training and Evaluation: Implement AI model training pipelines, fine-tune hyper parameters, and evaluate model performance using appropriate metrics. Continuously improve models through experimentation and iteration. - Deployment and Integration: Integrate AI models into existing systems and applications, ensuring scalability, efficiency, and reliability. Collaborate with software engineers to deploy AI solutions in production environments. - Research and Innovation: Stay up-to-date with the latest advancements in AI technologies, research papers, and frameworks. Identify opportunities to leverage new techniques and tools to enhance AI capabilities within the organization. - Performance Optimization: Optimize AI models for resource usage, inference speed, and memory footprint, considering edge computing and real-time processing requirements. - Data Privacy and Security: Ensure compliance with data privacy regulations and implement security measures to safeguard sensitive data used in AI applications. - Collaboration: Collaborate with cross-functional teams, including data scientists, developers, and domain experts, to understand requirements, provide insights, and deliver AI-driven solutions. - Documentation: Create clear and concise documentation of AI models, methodologies, and implementation details for knowledge sharing and future reference. - Continuous Learning: Proactively engage in professional development activities, attend conferences, workshops, and webinars to enhance expertise in AI and related technologies.