职位名称：数字后端设计工程师

职位描述：
根据个人情况和公司项目规划，承担如下一种或多种职责：
1. 完成编写时序约束，编写低功耗设计文件（UPF/CPF），逻辑综合/物理综合，形式验证，静态时序分析，功耗分析，低功耗设计规则检查（CLP）；
2. 完成布局规划，电源规划，布图布线，物理验证，电压降分析，电迁移分析；
3. 完成DFT逻辑设计和验证，完成编写DFT模式时序约束，帮助DFT模式时序收敛，帮助芯片bring-up，完成测试向量的调试，良率的提升；
4. 探索并引入AI/ML辅助EDA工具（如智能时序预测、自动布局优化、功耗智能调优等），提升后端设计流程的效率与结果质量；
5. 参与或主导基于机器学习的数据分析项目，辅助参数预测、异常检测或时序建模等；
6. 为客户/现场应用工程师/销售人员提供技术支持。

职位要求：
1. 电子工程硕士或更高学历；
2. 具备以下单项或多项经验：从RTL到GDS的设计实现，芯片级测试，ASIC编码和模拟，ASIC物理版图，集成电路制造和工艺；
3. 对人工智能/机器学习在芯片设计中的应用有兴趣或实践经验（如使用过ML工具包、了解时序/功耗预测模型、自动化脚本优化等）；
4. 具备基础的数据处理和编程能力 （如Python/Tcl/Perl）， 能够利用AI框架 （如TensorFlow/PyTorch）进行简单的模型训练或推理；
5. 能够熟练使用AI工具辅助研发工作者优先；
6. 富有事业心和团队合作精神，良好的中英文听说读写能力。

工作地点：上海/成都/南京

Title: Physical Design Engineer

Responsibilities:
You will be in a position responsible for one or more of below assignments:
1. Complete writing timing constraint, writing UPF/CPF, logic/physical synthesis, formal verification, STA, power analysis, CLP.
2. Complete floorplan, power plan, P&R, physical verification, IRDrop analysis, EM analysis.
3. Complete DFT logic design and verification, writing DFT mode timing constraint, support DFT mode timing closure, support chip bring-up, complete test pattern debugging and yield improvement.
4. Explore and introduce AI/ML assisted EDA tools (e.g., intelligent timing prediction, automated placement optimization, smart power tuning) to improve the efficiency and quality of the physical design flow.
5. Participate in or lead machine learning based data analytics projects to support parameter prediction, anomaly detection, and timing modeling, among others.
6. Provide technical support for customer/FAE/sales.

Requirements:
1. Master's or above degree in EE.
2. Have following single or multiple experiences: design implementation from RTL to GDS, chip level testing, ASIC coding and simulation, ASIC physical layout, IC manufacture and process.
3. Interest or hands-on experience in applying AI/ML to chip design (e.g., using ML toolkits, understanding timing/power prediction models, automated script optimization).
4. Basic data processing and programming skills (e.g., Python/Tcl/Perl), with the ability to use AI frameworks (e.g., TensorFlow/PyTorch) for simple model training or inference.
5. Familiarity with AI tools applied in R&D is preferred.
6. Self-motivated and a good team player. Good communication skills in both Chinese and English in either listening, speaking, reading or writing.

Location: Shanghai/Chengdu/Nanjing