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Siemens RD for skill analysis test-campus in YANCHENG, China

Job Family: Sales

Req ID: 436315

  1. Positioning:Undertake algorithm development work in the field of industrial automation, including machine learning, deep learning, reinforcement learning, etc.

  2. Job responsibilities:

  3. Responsible for product technology development, including technical problem-solving and optimization throughout the product lifecycle.

  4. Innovatively design competitive algorithm solutions and develop their implementation based on practical application scenarios.

  5. Conduct research and tracking of cutting-edge technologies in the AI field to ensure the advancedness and rationality of design solutions.

  6. Collaborate with R&D personnel from other departments to integrate ML/AI algorithm development achievements with practical hardware/system processes, creating competitiveness for automation products.Qualifications:

  7. Full-time Master's degree in computer science, electronics, mathematics, mechatronics, or related fields.

  8. CET6 or above, proficient in reading English literature, with a good mathematical foundation.

  9. Sufficient theoretical foundations and rich R&D experience in deep learning and machine learning, proficient in using mainstream frameworks such as TensorFlow, PyTorch, Scikit-learn, lightGBM, etc.

  10. Proficient in programming languages such as C/C++/Python, familiar with commonly used algorithms in machine learning/deep learning/reinforcement learning.

  11. Skilled in problem analysis and solving, with innovative and learning abilities, and a good spirit of teamwork.

  12. Candidates with skills in algorithm hardware deployment, especially embedded deployment, lightweight optimization, model quantization, etc., are preferred.

  13. Familiarity with general large-scale model training and transfer learning, distributed training techniques; familiarity with reinforcement learning, policy optimization algorithms; preference for candidates with expertise in fault diagnosis, predictive maintenance, and other application algorithms.

  14. Priority given to candidates with practical project experience or high-level original achievements.

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