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西门子 数字化工业 AI 计算机视觉研究员 Computer Vision Researcher

Job Description

Position Overview

This position develops machine vision 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 vision technologies (e.g. few shot learning, object detection, semantic segmentation, deep generative model). 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.

Responsibilities

·       Working with business unit (e.g. product managers, business development, system architects) to identify machine vision use cases and understand requirements.

·       Implementation of proofs of concept, and investigation and implementation of different solution alternatives.

·       Investigation of the latest machine vision technologies and assessment of their benefits.

·       Application of AI technologies to real-world problems in industrial use cases (e.g. robots enhancement, quality inspection, vision based control etc.)

Required Knowledge / Skills, Education, and Experience

·       Strong independent machine vision 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 image processing (edge detection, etc.), machine vision(object detection, semantic segmentation, few shot learning, data augmentation) and deep learning (deep generative model, self-supervised learning, etc).

·       Familiar with scikit-learn, pytorch, tensorflow, numpy or other related frameworks/libraries.

·       Excellent interpersonal and communication skills in English (verbal & written).

 

Knowledge as a Plus

·       Rich Knowledge of statistic machine learning techniques (bayes modeling, graphical model, etc.)

·       Knowledge of reinforcement learning (model-based and model free RL, on- and off-policy learning, inverse-RL, etc.)

·       Knowledge of data efficient learning (metric-learning, meta-learning, transfer learning etc.)


#digital minds#



Organization: Digital Industries

Company: Siemens Ltd., China

Experience Level: Early Professional

Job Type: Full-time

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