About the role
Lead R&D applying AI/ML to manufacturing challenges such as process monitoring, quality improvement, and reconfigurable systems, developing scalable ML pipelines and advanced predictive models.
ResearchOnsite
Key Responsibilities
- Conduct research on ML/AI applications in smart manufacturing
- Develop and deploy ML pipelines using MLOps practices
- Work with time series data for predictive modeling
- Apply advanced ML methods including few-shot, transfer, and continual learning
- Collaborate with a multidisciplinary team
- Ensure scalable and reproducible ML workflows using Docker
Requirements
- PhD in Computer Science, Engineering, or related field with focus on ML/AI
- Proven experience deploying ML models in production environments
- Proficiency in time series analysis and quality monitoring systems
- Familiarity with Docker and MLOps best practices
- Knowledge of advanced ML techniques such as few-shot, transfer, and continual learning
- Strong Python programming skills and experience with ML frameworks like PyTorch or TensorFlow