Responsibilities
- Design, train, and refine machine learning and deep learning models to solve practical challenges in manufacturing operations.
- Construct robust data pipelines for data ingestion, cleansing, and transformation using platforms such as Spark or Databricks.
- Implement MLOps methodologies including version control, continuous integration and deployment, monitoring, and automated retraining to maintain production-ready AI systems.
- Explore and apply advanced AI technologies like large language models, retrieval-augmented generation, vector databases, and generative AI for scalable solutions.
- Deploy and integrate machine learning models within enterprise platforms such as ERP, MES, and IoT ecosystems to ensure smooth interoperability.
- Continuously monitor, evaluate, and enhance model performance to ensure high accuracy, reliability, and operational efficiency.
- Work collaboratively with data engineers, system architects, and domain specialists to develop solutions that align technical capabilities with business objectives.
- Promote ethical AI development by ensuring fairness, explainability, and regulatory compliance in all model design and deployment stages.
