面議（經常性薪資達4萬元或以上） 新北市土城區 5年工作經驗 今天剛更新
＜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)
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