Kaiku_開酷科技股份有限公司

1. 協助工程師IC電氣特性及功能驗證測試. 2. 協助工程師IC可靠度驗證測試 3. 協助工程師測試數據的整理及分析 4. Proficient with electronic welding skills. Skill any of the following is a plus: Any college students in electrical engineer related field. Patience and attentive are preferred. Basic Excel skills are required Have flexible schedule. Self-motivated and aggressive to learn. Please bring relevant transcript to the interview. KaiKuTek is the world's leading provider for 3D gesture sensor using mmWave Radar with embedded AI accelerator. We possess key technologies in areas such as Antenna-in-Package (AiP), ML algorithm, AI accelerator, as well as 60 GHz radar transceiver design. With recent merger by JMicron, founded in 2001 and located in Hsinchu Science Park, our product portfolio expands to high speed SerDes bridge controller SOC's mainly in storage application utilizing USB, PCIe, and SATA. This new sensing technology will change and redefine human-machine interface as we know today, and mmWave technology combined with high speed SerDes will open door to many new possibilities and application frontiers. KaiKuTek is looking for enthusiastic test Intern engineers willing to take upon new challenges of working closely with cross functional teams, including digital IC designers, analog/RFIC designers, firmware engineers, packaging engineers, production and testing as well as marketing and FAE, to optimize the overall SoC performance in terms of power, area, functionality, testability as well as to create proof-of-concept for new customer engagement.

We are seeking a highly motivated and experienced Senior Deep Learning Engineer to join our innovative team. In this role, you will contribute to designing, implementing, and optimizing cutting-edge deep learning models for radar applications. Specifically, you will work on advanced deep learning solutions that integrate mmWave radar signal processing with state-of-the-art algorithms. Additionally, you will mentor junior engineers and collaborate with cross-functional teams to drive the boundaries of both Radar sensing and AI technology forward. About KaiKuTek KaiKuTek is a global leader in 3D gesture sensing solutions powered by mmWave radar and embedded AI accelerators. We specialize in key technologies, including Antenna-in-Package (AiP), machine learning algorithms, AI accelerators, and 60 GHz radar transceiver design. Following our recent merger with JMicron Technology Corp., a company founded in 2001 and headquartered in Hsinchu Science Park, we have expanded our product portfolio to include high-speed SerDes bridge controller SoCs for storage applications utilizing USB, PCIe, and SATA technologies. Our innovative sensing technology redefines the human-machine interface, combining mmWave radar with high-speed SerDes to unlock new possibilities and application frontiers. Key Responsibilities • Design, develop, and deploy deep learning models for advanced radar applications, requiring computer vision and digital signal processing expertise. • Optimize and fine-tune models for performance, robustness, and deployment on edge or embedding devices. • Collaborate with data scientists, software engineers, and validation teams to understand requirements and deliver high-quality solutions. • Build and maintain tools and pipelines for data preprocessing, model training, evaluation, and deployment. • Stay updated on the latest trends and advancements in AI and deep learning technologies. • Write clear, efficient code following the best software engineering and machine learning practices. • Mentor and guide junior engineers to foster technical growth within the team. Qualifications • Required: o Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. o 2+ years of experience in deep learning and AI model development. o Strong proficiency in PyTorch deep learning framework. o Proficiency in Python and relevant machine learning libraries. o Strong understanding of neural network architectures, training techniques, and optimization algorithms. o Strong problem-solving skills and the ability to work on challenging technical problems. o Excellent communication and collaboration skills. • Preferred: o Experience with deploying deep learning models on production systems. o Familiarity with model quantization, pruning, and optimization for edge devices. o Knowledge of MLOps tools (e.g., MLflow, Kubernetes, Docker) for model lifecycle management.