Identify data-driven opportunities to enhance product recovery.
Develop automation solutions that improve engineering analytical efficiency.
Apply statistical, machine learning, and AI-Enabled methodologies to generate actionable insights.
Evaluate emerging Artificial Intelligence technologies for relevant engineering and manufacturing use cases.
- Project Scope
- The intern will be given the opportunity to:
Retrieve, prepare, analyze, and visualize manufacturing data to evaluate NAND component test-flow efficiency and product recovery opportunities.
Work with SpecTek engineers to understand test-flow challenges and apply structured, data-driven problem-solving methodologies.
Develop scripts, analytical models, reports, and automation solutions using relevant programming languages, statistical tools, and data platforms.
Apply statistical analysis, machine learning, enterprise AI tools, and prompt-engineering techniques to accelerate data exploration, knowledge retrieval, documentation, and insight generation.
Evaluate AI-Enabled solutions for engineering use cases, validate AI-generated outputs, and follow applicable data security, governance, and responsible AI requirements.
- Learning Opportunities
- The intern will have the opportunity to:
Gain practical exposure to NAND component testing, product recovery, and manufacturing data analysis.
Develop proficiency in programming, data preparation, statistical analysis, machine learning, automation, and visualization.
Learn how AI-Enabled tools and prompt-engineering techniques can be applied responsibly within engineering workflows.
Build experience in validating analytical and AI-generated outputs, documenting assumptions, and communicating limitations.
Strengthen critical thinking, technical documentation, stakeholder communication, and cross-functional collaboration skills.