We are the Asia Media Development Organization (AMDO), responsible for replicating the most advanced Heat-Assisted Magnetic Recording (HAMR) media for qualification and ensuring its manufacturability at high production volumes. Our team achieves this by focusing on Head-Disk-Mechanical (HDM) tribology, contamination control, and defect reduction, working closely with the sustaining organization.
About the role - you will:
As an intern, you will join a collaborative, cross-functional team to design, prototype, and deploy intuitive GenAI tools for analytical applications and predictive models. You will work closely with media development engineers to assess the engineering requirements and jointly develop AI solutions to address these needs. This internship offers the opportunity to apply your engineering background and Python skills in the development of generative AI applications. Your responsibilities will include :
- Developing working prototypes, rigorously testing and validating AI models, and deploying these models into relevant workflows.
- You will actively solicit and incorporate engineering feedback to continuously improve model performance and adjust model functionality, ensuring alignment with project goals.
- This role also provides the opportunity to collaborate with the GFIT organization on projects requiring more advanced Agentic AI systems, providing valuable experience in cutting-edge AI development.
You will contribute to Agentic AI projects that aim to:
- Automate Daily Performance Reporting: Develop AI agents to automatically generate daily performance summaries, highlighting yield performance for individual builds and identifying anomalies for engineering review and failure analysis.
- Streamline Data Analysis: Create tools for automated data parsing, statistical plotting, and in-depth analysis of material characterization results, accelerating the experimental process.
- Enhance Process Understanding: Build AI systems that analyze machine process outputs, identify key dependencies, and reveal interactions to provide engineering teams with deeper insights into the fundamental physics driving observed responses.
- Optimize Machine Performance: Develop intelligent agents for sputter, front-end, and back-end processes that compare machine run logs against key performance indicators (KPIVs) to ensure correct machine settings and proactively detect or predict performance anomalies during sputter runs.
- Predict Media Performance: Construct predictive models that leverage sputter machine key process output variables (KPOVs) to forecast media performance metrics and critical thicknesses, enabling proactive process adjustments.
- Create AI-powered coding assistants that enable the development of advanced user interfaces featuring interactive plotting and natural language-driven analysis.
About you:
We are seeking candidates who are passionate about AI and eager to explore the application of Generative AI in real-world industrial settings. With a solid foundation in engineering, chemistry, or physics, and experience with Python programming to develop AI/Agentic AI solutions for automating workflows and analyses. You should possess:
- Self-Motivation & Planning: Demonstrated self-initiative and the ability to independently initiate projects, logically outlining step-by-step processes to achieve goals.
- Collaboration & Communication: Strong communication and problem-solving skills, with the ability to thrive in a collaborative, cross-disciplinary team environment.
- Intellectual Curiosity: A curious, inventive, and eager-to-learn mindset.
- Adaptability: Comfort and ability to work both independently and collaboratively in a fast-paced environmen
Your experience includes:
- Currently pursuing a Bachelor's or Master's degree in a core engineering science (e.g., Physics, Electrical Engineering, Mechanical Engineering, Material Science, Chemistry).
- Possess a strong understanding of basic sciences (e.g., electrical, mechanical engineering, physics, chemistry, and material science) and have at least a modest background in programming (e.g., Python, JMP, or MATLAB)
- Moderate level of proficiency in Python programming (e.g., able to write scripts for data manipulation and basic model building) and familiarity with Generative AI frameworks (e.g., OpenAI API, FastAI).
- Knowledge of machine learning, deep learning, and natural language processing concepts.
