AI Technology EngnieerAI 技术 工程师
此职位的主要义务和职责 Listing of the key duties and responsibilities performed by the job
1. System Development:
a. Design, develop, and deploy CV and RPA algorithms and systems to semiconductor assembly quality control and automation.
b. Develop and integrate generative AI models to generate, simulate, or optimize manufacturing processes.
2. System Quality Assurance:
a. Implement real-time image analysis systems to detect, classify, and track defects in semiconductor components and assemblies.
b. Utilize AI techniques to analyze data and provide predictive insights for quality assurance.
3. Data Analysis and Model Training:
a. Analyze visual and operational data to identify trends, patterns, and areas for improvement in manufacturing processes.
b. Train and optimize machine learning models using extensive datasets to enhance accuracy and performance.
4. System Integration:
a. Integrate computer vision and AI solutions with existing manufacturing systems and platforms to ensure seamless operation.
b. Collaborate with hardware engineers to ensure compatibility and robustness of computer vision setups.
5. Documentation and Reporting:
a. Create detailed technical documentation for developed systems, including specifications, user guides, and training materials.
b. Present findings, recommendations, and performance metrics to management and relevant stakeholders clearly and compellingly.
6. Continuous Improvement:
a. Stay abreast of advancements in computer vision, generative AI, and manufacturing technologies.
b. Propose innovative solutions and process enhancements to maximize efficiency and product quality.
1. 系统开发：
a. 设计、开发和部署 CV 和 RPA 算法和系统，用于半导体组装质量控制和自动化。
b. 开发和集成生成式 AI 模型，以生成、模拟或优化制造流程。
2. 体系质量保证：
a. 实施实时图像分析系统，以检测、分类和跟踪半导体元件和组件中的缺陷。
b. 利用 AI 技术分析数据并提供预测性见解以保证质量。
3. 数据分析与模型训练：
a. 分析视觉和运营数据，以确定制造流程中的趋势、模式和需要改进的领域。
b. 使用广泛的数据集训练和优化机器学习模型，以提高准确性和性能。
4. 系统集成：
a. 将计算机视觉和 AI 解决方案与现有的制造系统和平台集成，以确保无缝运行。
b. 与硬件工程师合作，确保计算机视觉设置的兼容性和稳健性。
5. 文档和报告：
a. 为开发的系统创建详细的技术文档，包括规格、用户指南和培训材料。
b. 清晰而令人信服地向管理层和相关利益相关者展示调查结果、建议和绩效指标。
6. 持续改进：
a. 紧跟计算机视觉、生成式 AI 和制造技术的进步。
b. 提出创新解决方案和工艺改进，以最大限度地提高效率和产品质量。
任职资格Qualifications
教育背景Education
1. Master’s degree in computer science, Electrical Engineering, Robotics, AI, or a related field.计算机科学、电气工程、机器人技术、人工智能或相关领域的硕士学位。
知识Knowledge
*职位要求的信息或知识范围 Statement of the Informational or conceptual framework required by the Job
1. Proficient in programming languages such as Python, C++, or Java relevant to computer vision and AI applications.
2. Experience with computer vision libraries (e.g., OpenCV, TensorFlow, Keras) and generative AI tools (e.g., GANs, VAEs).
3. Understanding of machine learning algorithms, especially in image processing and automated decision-making.
1. 精通与计算机视觉和 AI 应用相关的编程语言，如 Python、C++ 或 Java。
2. 具有计算机视觉库（例如 OpenCV、TensorFlow、Keras）和生成式 AI 工具（例如 GAN、VAE）的经验。
3. 了解机器学习算法，尤其是在图像处理和自动决策方面。
相关工作经验Experiences
Experienced candidates, Semiconductor Engineering working experience is a plus.
Experience in computer vision applications and Gen-AI development or a related field.
Familiarity with generative AI frameworks and methodologies Relevant certifications in computer vision, artificial intelligence, or machine learning (AWS Certified Machine Learning, Google AI certification) are a plus.
有经验的候选人，有半导体工程工作经验者优先。
具有计算机视觉应用程序和 Gen-AI 开发或相关领域的经验。
熟悉生成式 AI 框架和方法计算机视觉、人工智能或机器学习方面的相关认证（AWS 认证机器学习、Google AI 认证）是加分项。
其他胜任力Competencies &Soft Skill
1. Good English skill, both written and oral
2. Good teamwork spirit
Strong self-learning motivation, good communication skill.
1. 良好的英语书面和口头表达能力
2. 良好的团队合作精神
较强的自学动机，良好的沟通能力。