Role overview
* Architect scalable, high-performance AI/ML solutions for predictive maintenance, and real-time analytics.
* Develop AI strategies aligned with business goals, focusing on industrial IoT (IIoT) and edge computing.
* Design robust data pipelines and model deployment frameworks.
* Deep understanding of machine learning algorithms, statistical modeling, and AI techniques, including deep learning, reinforcement learning, and NLP.
* Build and optimize machine learning models using Python, TensorFlow, PyTorch.
* Implement and manage MLOps strategies, processes, and tools for continuous integration, deployment, and monitoring of ML models
* Oversee the deployment of ML models into production environments, ensuring they are scalable and performant.
* Ability to analyze business problems and design AI-driven solutions to address them.
* Develop algorithms and techniques to enhance the accuracy, reliability, and performance of models in real-world applications.