Collaborating with multidisciplinary teams in the definition of new AI-Powered Engineering workflows for Product Optimization and Simulation (in terms of performance, manufacturability, controllability)
Leading technical development of research and development projects on the combination of AI and engineering methodologies
Developing and integrating software components for AI applications according to customer and technical requirements
Checking availability and relevance of internal and external data sources
Proposing, and leading new data collection activities
Cleaning and validating data
Working with AI Product Owners to define project technical goals and requirements, AI Engineers to define the project software architecture and maintenance/retraining strategy and SME's to adapt AI technology to the industry needs
Requirements
Master or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field
Experience in defining the technical requirements and expectations of AI solutions for engineering applications
Deep understanding of Machine Learning and AI algorithms for regression, classification and anomaly detection tasks applied to tabular data with uncertainty quantification and explainability requirements
Proven experience of applying AI algorithms for dynamical data sources (time series) regression, clustering, anomaly detection and uncertainty quantification
Experience in combining models with data from different sources and hybrid modelling approaches
Experience in defining models for 3D/Graph data types
Proven experience with optimization algorithms (e.g. gradient based, model based, non-parametric for parametric and non-parametric inputs) and active learning
Experience with traditional control algorithms calibration, MPC and RL
Software programming languages including Python, C++
Benefits
Contemporary work-life balance policies and wellbeing activities
Comprehensive private medical care options
Safety net of life insurance and disability programs
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