This position develops AI solutions and proofs of concept in the field of industrial production and engineering systems. As part of an innovative team you perform applied research with a focus on Machine Learning technologies (e.g. Deep Reinforcement Learning, Time Series Prediction ). Thereby, close collaboration with the business units of Siemens Digital Industries is required.
This is a position within a new agile team of Technology & Innovations department of Siemens Digital Industries, Factory Automation.
· Working with business unit (e.g. product managers, business development, system architects) to identify AI use cases and understand requirements.
· Implementation of proofs of concept, and investigation and implementation of different AI solution alternatives.
· Investigation of the latest AI technologies and assessment of their benefits.
· Application of AI technologies to real-world problems in industrial use cases (e.g. automation, control, etc.)
Required Knowledge / Skills, Education, and Experience
· Strong independent AI technical survey ability and implementation skills. Able to review and implement state of art.
· Good at source code reading and incremental development ability
· Strong programming skills (Python is a must)
· Good mathematics understanding (linear algebra, probability and statistic, convex optimization)
· Knowledge in both classic machine learning and deep learning
· Knowledge in (deep) reinforcement learning related algorithms (model-based and model-free RL, on- and off-policy learning, inverse-RL, etc.), understand the design motivations of these algorithms.
· Familiar with scikit-learn, pytorch, tensorflow or other related frameworks/libraries.
· Excellent interpersonal and communication skills in English (verbal & written).
Knowledge as a Plus
· Knowledge of advanced control/robotics such as (MPC, LQR, Bayesian Filter/Smoother, etc.)
· Knowledge of data efficient learning (metric-learning, meta-learning, etc.)
Organization: Digital Industries
Company: Siemens Ltd., China
Experience Level: Early Professional
Job Type: Full-time