AI Solution Development: Responsible for providing intelligent solutions to manufacturing and business problems using machine learning, deep learning, and generative AI methodologies.
R&D Innovation: Analyze and prototype new AI technologies and frameworks to solve complex challenges, staying at the forefront of industry trends.
Infrastructure for AI: Manage and optimize the specialized IT infrastructure and GPU-accelerated environments needed to train and deploy large-scale AI models.
Testing & Model Validation: Develop and perform rigorous tests on AI applications, including data validation, model performance benchmarking, and troubleshooting bias or accuracy issues.
CI/CD for Machine Learning (MLOps): Implement and support MLOps pipelines to automate the training, versioning, and deployment of models (Continuous Integration and Continuous Delivery).