Failure Analysis Intern
Undergrad or master's in AI/Computer Engineering/Data Science/IS/EE; programming with Python and Jupyter Notebook; experience with AI/ML and large language models; ability to develop automation, classification, and user interfaces for failure analysis workflows.
Job Description
In your new role you will:- Process Understanding:Understand Failure Analysis process, catalogues and various failure modes / mechanism.
- Tool Application:Understand VFA flow and apply different tools (search engines, RPA).
- AutomationDevelopment:Create programming to automate job labelling process.
- Customization:Customize job labelling process for different FA groups.
- Classification:Catergorize failure mode through AIML classification.
- Interface Design:Develop user interface to facilitate Man-machine interaction for above items.
- Deployment Collaboration:To collaborate with IT to deploy end user coded App into operational database.
- Knowledge Acquisition:Gain knowledge on FA process, failure modes and classification.
- DigitalTransformation Insight:Good understanding of future digitalization in FA with Virtual Failure Analysis process and job labelling.
- Tool Exposure:Exposure to use of search engine for topic consolidation, cumulative learning of FA insights.
- Application Development:Develop end user APP for digital automation of FA processes.
- SkillBuilding:Project management skill. Career Advancement: Gain industry working experience to ease future career.
Your profile
You are best equipped for this task if you have:- Educational Background:Undergrad or master in Artificial Intelligent (AI engineering) / Computer Engineering / Data science / Information System / EE / EEE with relevant AI oriented mindset.
- Programming Proficiency:Knowledge in Language programming (eg. Python, Jupiter Notebook) AI & ML.
- Expertise:Knowledge in Artificial Intelligent Machine Learning, Large Language Model (LLM).
- Adaptability & Learning Agility:Interactive and dynamic in learning different failure analysis process flow.
Contact:
Hillary Woo
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