Artificial Intelligence Engineer

3 days ago

Kuala Lumpur, Kuala Lumpur, Malaysia Texas Instruments Full time $120,000 - $180,000 per year

About the Job

The AI Engineer will drive implementation of artificial intelligence and machine learning solutions to enhance semiconductor back-end manufacturing operations. The role will involve close collaboration with manufacturing teams, data scientists, product and process engineers to identify opportunities and implement AI-driven solutions that improve operational efficiency, quality, and yield. This position requires a strong understanding of AI/ML technologies, experience with semiconductor manufacturing, and a passion for applying data-driven techniques to solve complex industrial problems.

Responsibilities include:

  • Collaborate with cross-functional teams and domain experts to identify opportunities for AI integration in workflows.
  • Build and maintain ETL/ELT pipeline to OLAP system.
  • Analyze large datasets from manufacturing equipment, sensors, and logs to enable effective machine learning applications.
  • Lead proof-of-concept projects and pilot programs to demonstrate the value of AI applications in manufacturing settings.
  • Develop and deploy AI/ML solutions for workflow automation, defect detection, yield improvement, process optimization, and predictive maintenance in semiconductor back-end manufacturing processes.
  • Provide technical documentation, training, and support to ensure seamless adoption of AI solutions by production teams.
  • Monitor AI systems performance and implement enhancement.
  • Stay updated with the latest advancements in AI/ML and propose innovative solutions applicable to semiconductor manufacturing.

Minimum requirements:

  • Master's or Ph.D. in Artificial Intelligence, Machine Learning, Data Engineering or related disciplines.
  • Experience in advanced computer vision techniques, such as deep learning for image classification, segmentation and object detection.
  • Experience in LLM, Context Engineering, RAG, Knowledge Graph and LLM fine-tuning.
  • Experience in AI model explainability, trustworthiness, and validation in industrial contexts.
  • Knowledge of semiconductor back-end manufacturing processes, including assembly, packaging, and testing.
  • Experience in working with semiconductor manufacturing data, including sensor data, equipment logs, and MES data.
  • Familiarity with industry standards and protocols (e.g., SECS/GEM standards for semiconductor equipment).
  • Familiarity with data analysis tools and techniques.
  • Proven track record of publications, patents, or conference presentations in AI/ML applications for manufacturing.

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