數據工程師 (Data Engineer)

1.車用ADAS 攝影鏡頭、光達、雷達相關應用 

2.建立感知融合策略經驗(Camera Radar/Camera 

3.點雲物件辨識模型建立 

4.串接自動駕駛模擬器與系統驗證開放式平台之軟硬整合 

5.配合開發流程撰寫相關文件 

6.熟悉以下語言/ 一項或多項))：C++/Python/TensorFlow/PyTorch 程式開發能力，具ROS2 相關開發經驗尤佳 

7.主管交辦事項

＜About the job＞  

As the AI Software Engineer, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). 

＜Job Description＞ 

Responsible for deploying the AI/Data Science collaborative framework and building the AI model and data operating infrastructure. Using software development experience to design and develop high-performance automated systems for AI development and operation. As below: 

．Collaborating with Data Scientist/AI ML Engineer team, other software system development teams, and the infrastructure team. 

．Ability to utilize various tools/methods to build the MLOps/DataOps/DevOps and deploy and manage the AI Development framework and infrastructure 

．Developing infrastructures for data transformation and ingestion and automating important infrastructure to process data 

．Deploy AI models to the Inference server and optimize the performance of the model serving operation reliably and efficiently. 

．Assist the Data Scientist/AI ML Engineer team in converting the AI models into APIs to serve other systems or integrate with other systems. 

＜Skill Sets＞ 

(1)Excellent problem-solving and troubleshooting skills. 

(2)Genuine passion for learning new technologies and open-source projects. 

(3)Familiarity with Python and Java (python is a must) 

(4)Good understanding of the Linux OS environment, the Shell Scripting, and infrastructure/networking knowledge.  

(5)Experience with GitLab CI/CD 

(Nice to have but not necessary)  

(1)Experience with MLops and Model Serving tools. 

(2)Experience in GPU programming and performance tuning 

(3)Being familiar with AZURE (or AWS) cloud infrastructure will be a plus 

(4)Familiar with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s)

＜About the job＞ 

As the AI Project Manager and System Analyst, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. In addition to developing intelligent applications via related AI and Advanced Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging AI applications based on different use cases and expand your tech skillset in this world-class company. 

＜Job Description＞ 

*Type1：AI Project Manager 

Manages AI-focused projects from initial planning to delivery, ensuring alignment with business goals and promoting innovation. Responsibilities include coordinating cross-functional teams, allocating and optimizing resources, and maintaining project schedules and budgets. The role requires proactive problem-solving to address project challenges and mitigate risks while driving effective communication across departments. 

＜Qualifications＞ 

1. Over 5 years of experience in software project management, with a strong background in Agile methodologies. 

2. Highly proactive, self-motivated, and accountable. 

3. Willing and able to travel internationally for approximately 1-2 months per year. 

＜Required Skills＞ 

1. Strong understanding of the project lifecycle, including planning, execution, monitoring, and closure. 

2. Proven ability to manage project timelines, budgets, and resources effectively, ensuring projects are completed on schedule and within budget.t. 

3. Ability to communicate effectively with individuals from different departments and roles and coordinate resources. 

4. Strong analytical and problem-solving skills, with the ability to swiftly assess complex issues and implement solutions. 

5. Mastery of Microsoft Office programs (Word, Excel, PowerPoint) 

(Nice to have, but not necessary) 

1. Familiarity with manufacturing processes 

2. Possession of project management certifications such as PMP or Scrum. 

3. Intermediate or above English proficiency in listening, speaking, reading, and writing. 

*Type 2：AI System Analyst 

Responsible for gathering and analyzing the requirements and contributing to designing, developing, testing, and deploying in all phases of the AI system development project lifecycle, as below： 

1. Collaborate with business data analysts to analyze user requirements and ensure that requirements and acceptance criteria satisfy user needs. 

2. Create a system requirement specification to elaborate on system design, system components/interfaces, and data schema. 

3. Work with the multi-functional engineering team(e.g., data scientist, AI/ML engineer, data engineer, AI software engineer..., etc.) to ensure technical feasibility. 

4. Drive usability and quality of the AI system developed and ensure all system requirements are well implemented. 

5. Work on various enterprise AI system applications and problems, and analyze issues to identify root causes and prevention. 

6. Create the Wireframes(or UI Prototypes) for AI system feature discussion with users and provide them to the UI/UX design team. 

7. Author and update internal documentation; initiate and deliver requirement specification and system analysis/system design documentation. 

＜Required Skills＞ 

1. Practical experience in requirements gathering and analysis and change management 

2. Experience co-working with front-end and back-end system development teams. 

3. Strong analytical, verbal, and written communication, teamwork, and highly collaborative skills. 

4. Experience with Microsoft Visio, Axure RP(or other wireframe tools). 

5. Mastery of Microsoft Office programs (Word, Excel, PowerPoint) 

(Nice to have, but not necessary) 

1. Mastery of QA methodology and problem-solving tools/techniques in software engineering. 

2. Knowledge of AI/Data Science Tech(e.g., Machine Learning, Deep Learning, Statistics, Quantitative modeling techniques). 

3. Practical experience in Relational DB (e.g., MS SQL, PostgreSQL) and ability to write SQL queries.