Software Engineer (Systems) 3

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 (C...