Job Summary
Deeply understanding customer requirements and using computer vision and machine learning/deep learning technology to offer solutions. Responsible for work with Bosch internal partner to invent, design and develop computer vision/machine learning algorithms for AOI_ automatic optical inspection and AI for process optimization project as well as data mining.
Roles and Responsibilities
- Work together with/ lead project team to understand and analyze customer requirements, and pre-evaluate project deliverables and benefits.
- As Data scientist accompany the entire development process from the proof of concept to the serial implementation of the algorithms. Together with internal development partners you develop innovative solutions across the entire chain from the raw data to the function.
- Design and implement architectures to adopt appropriate approaches of AI / machine learning to ensure quality of data, self-learn pattern and trend, identify operational processes which can be automated and put into execution, and improve system operational efficiency.
- Collaborate with IT/machine/product technical experts to define data collection, storage, and process concept.
- Coordinate AI related work packages in RBCD in manufacturing areas
- Support on developing understanding and competence of machine learning/deep learning
- Support production area for data mining project such as smart testing and multi-correlational analysis.
- Master in computer vision, image processing, machine learning, deep learning
- More than 3 years working experience in real projects
- Willingness to take challenges, passion to solve problem in a systematic way
- Excellent at python, familiar with at least one of the frameworks: TensorFlow, pyTorch
- Familiar with classic image processing (eg. Image filter, edge detection, feature extraction, camera calibration…) and machine learning algorithms, good at opencv and deep learning for image processing (object classification, object detection, Segmentation…)
- Familiar with deep learning models. Eg: CNN, RNN, LSTM, Transformer…
- Familiar with deep learning area, latest achievement in the computer vision. Deep understanding of the deep learning network eg. AlexNet/VGG/ResNet/DeseNet/NIN/MobileNet, and the computing power/resource bottleneck of the network.
- Familiar with object detection framework and method, eg: SSD, Yolo, Faster-RCNN…
- Familiar with large language model related technics.
- Familiar with tool chain of data labelling, data management
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